Media Optimization Can Improve Glycosylation Patterns and Consistency to Impact Protein Efficacy

Glycosylation is affected by several factors, including: movement of the protein through the ER and Golgi apparatus, environmental factors, and sugar availability.  The movement of protein through ER and Golgi apparatus can be affected by cholesterol and other free fatty acid availability that impact health of ER and Golgi membranes.  Environmental factors include cell culture parameters such as pH, CO2, dissolved oxygen.  Sugar availability is driven by the media constituents and any feeds that are used.  Finally, lot-to-lot variation in commercially available supplements and feeds also introduce variation in glycosylation. It is important to select vendors and materials that have proven lot-to-lot consistency.

The wide variety of  factors impacting glycosylation can make controlling the quality profile a complex challenge.  Further, these same factors that drive post-translational modification also impact protein titer.  In many cases scientists will focus optimization efforts on either titer or glycosylation first, but find that both titer and glycosylation are affected by any one change.  In some cases, scientists will have to make a hard choice between quality and yield.  It is possible to focus on the physiology of the cell and target the ER and Golgi to increase both titer and consistency.

You ask an interesting question.  We did see the same effect of increased consistency in two different media bases when adding Cell-Ess.  Interestingly as you imply there were two different glycosylation patterns because the constituents in the base media were different but the increase in consistency of the glycoform patterns within each group remained the same.  We hypothesize that the effect would be similar throughout a variety of different media because the way Cell-Ess works is to improve the function of the Golgi and the ER which is one of the major drivers of glycan addition.  By improving the health of those organelles, the consistency will improve.

This is a complex question.  There are direct effects and indirect effects.  The direct effects are mostly driven by sugar mix, specifically what kind of sugar (ex. glucose or galactose) and what form it is in.  Additionally, there are many indirect effects that control the environment.  The amount of a certain amino acid such as glutamic acid in combination with glucose levels can lead to higher lactic acid and a pH change, which will affect the glycosylation pattern.  Further, if a base is used to increase the pH, then the osmolarity will increase, and that can also influence the glycosylation pattern.  There are amino acids, such as glutamine, that are more likely to lead to increases in ammonia, which will also influence the addition of glycans.  Outside of the standard media ingredients, scientists have used peptones from plants or yeast to influence the glycosylation patterns with varying results.  Another approach is to supplement with cholesterol and free fatty acids to increase the efficiency and functionality of the ER and Golgi.  The range of potential influencers on post-translational modification both direct and indirect are part of the reason for the complexity that is seen in this field.

Conceptually this questions addresses the issue of targeting a particular glycan profile.  It is true that there is a target profile for both innovator biologics and biosimilars.  For the biosimilars, the target is clear - it is the glycan profile of the innovator. For the innovator, in the case of antibodies, there may be a desire to target a profile that increases antibody-dependent cell-mediated cytotoxicity (ADCC) over complement-dependent cytotoxicity (CDC) or increases half-life of the antibody in circulation, or a certain profile may have been specifically targeted in R&D.  In some cases, the optimal candidate was chosen empirically during biological testing and then becomes the target profile.  In any scenario, glycan addition drives functionality, and this is true for both the innovator and the biosimilar.  In some cases, researchers have determined that the innovator glycan profile is not be the best and have developed therapeutics with improved glycan profiles.  These “improved” therapeutics are part of a relatively new class called bio-betters.

Glycosylation is a critical quality to consider for proteins.  The amount and type of glycosylation has dramatic effect on the physical nature of the protein and its biological function.  In addition to amino acid sequence, glycosylation can affect the folding of proteins and their ability to aggregate with each other.  The different folding and aggregate structures then have a resultant effect on stability and solubility.  The function is also affected in many ways by glycosylation, including the pharmacodynamics and pharmacokinetics of antibodies.  Antibodies with lower glycoforms can be cleared faster leading to a lower physiological half life.  The binding of the protein to the target is also affected in how long and how tightly it will bind.  Antigenicity can be impacted by glycosylation where certain glycoforms can increase antigenicity.  Amount of glycosylation addition and complexity of the glycoform both impact the protein, and there is a wide range of effects glycosylation can have these various protein characteristics.  In many cases, differential glycosylation effects can impact therapeutic efficacy of a protein.

The term glycoengineering has been changing over time.  Glycoengineering was traditionally defined as any tool used to modify or change the glycosylation patterns. There are 4 basic levers to pull to control the addition of glycans.  They are (1) the substrate - namely the sugar nucleotide mix and quantity, (2) the enzymes - glycotransferases and glycosidases, (3) the physical location where the additions occur - namely the ER and Golgi, and (4) the environment which can affect all of the other levers.  The early forms of glycoengineering used media components to shift the glycosylation patterns by adding a variety of sugars in addition to glucose.  Once the environmental parameters were shown to effect the glycosylation pattern, a new form of engineering developed in which parameters (such as pH and oxygenation) were monitored to target the profile of choice.  As technology has progressed, the specific genetic and protein targets became more clearly identified, and methods to specifically alter them have have been developed and utilized.  As an example, CRISPR can be used to make a specific genetic modification that would be beneficial for the particular biologic and glycosylation profile you are targeting.  The ideal strategy to optimize glycosylation pattern and achieve consistency would be to use a variety of engineering tools rather than utilizing an either/or strategy.  In our studies, we have looked at providing a method to improve the physical location where post-translational modifications occur - namely the ER and Golgi.  By targeting the physical structure, we have seen both an increase in the higher order glycoforms and increased consistency when Cell-Ess is used.

As mentioned, the approach with Cell-Ess is to target the physiological make-up of the ER and Golgi to effectively make them work more efficiently and function appropriately.  The hypothesis is if you are able to target the membrane constituents of the ER and Golgi, then there would be greater consistency and higher order glycoforms.  With the addition of Cell-Ess in two different media bases, we have seen increased consistency in the glycosylation pattern of monoclonal antibodies, suggesting that the Golgi is functioning more uniformly across groups to increase reproducibility.  Further, with the addition of Cell-Ess, we also observed increased galactosylation in two different base media, also suggesting more efficient Golgi.  The amount of glycoform G0F was decreased, masking the increase of fucosylation associated with higher order glycoforms, so the net result is a decrease in fucosylation.  In other work, we have shown a greater than 20% increase titer by increasing the amount of protein made per cell, which also points toward a more effective ER and Golgi.

It is a great question.  Cell-Ess does not have any effect on downstream purification.  We have not looked at the aggregation issue directly. However, in cases where we have increased titer, we have not seen an increase in aggregation.  We do hypothesize there may be a slight reduction in aggregation based on mechanism of action where the Golgi is functioning better.  A more properly functioning Golgi leads to correct protein folding and proper post-translational modification, and those factors can be removed from the complex aggregation equation.

The optimal way to start would be with a CD media and establish a baseline.  Once you have a baseline for your system, then CD supplements can be added individually to determine whether the profile changes.  If you are not able to change your profile with the CD supplements, then you can move to the cGMP non-CD supplements such as peptones.  If using peptones, you should try to find one with the most defined characteristics so you are able to reproduce your results.

Depending on the supplement, you can have a range of effects on your cells, from providing a broader base of sugar nucleotides to improving the function of the glycolytic enzymes.

There are many reasons for aggregation.  To simplify it, imagine there is the ability to formulate an equation to determine if and how much proteins will aggregate and at what concentration.  The formula would have many inputs.  Glycosylation is one of the many inputs that would determine whether a protein will aggregate.  In the case for monoclonal antibodies, as touched upon in an earlier question, glycosylation can affect stability and solubility.  If a monoclonal antibody is less soluble and less stable, then it will have a higher propensity to aggregate.  Furthermore, glycosylation also affects the folding of a protein.  In cases where the protein is mis-folded, the protein would also have a higher likelihood of precipitating.  While glycosylation can play a very important role in aggregation, it is one of many components.  Therefore, the amount, type, and location of the glycosylation will also be relevant.  How the aggregation equation is formulated may vary for each protein, but the basic inputs will be common between the equations.  Glycosylation and aggregation are related, but to what degree and how much would likely depend on your specific protein.

We have not specifically looked at other post-translational modifications such as lipidation.  Cell-Ess can improve the lipid membranes including those of the ER and Golgi. Therefore, theoretically there should be a benefit in using Cell-Ess for lipidated proteins, but we have not tested it yet.  Lipidation, similar to glycosylation, is a complicated multistep process where Cell-Ess can most likely play a role, but we look forward to hearing from users who have directly tested what their experiences have been.