Development of methods for in vivo quantification of proteolysis in E. coli expression systems
SUPERVISOR: Gerald STRIEDNER
PROJECT ASSIGNED TO: HANAEE AHVAZ Hana
Proteolysis is of central importance in recombinant gene expression. Degradation of miss-folded or damaged proteins is usually mediated by different proteases and it also may take place in different cell compartments. Proteolysis, central for full functionality of a living cell, is controlled via complex regulatory networks and both, the abundancy as well as the activity of individual proteases, strongly depend on the cellular state and environmental conditions. Mis- or unfolded but also correctly folded recombinant protein is exposed to these proteases and thus product degradation occurs. Degradation of recombinant protein during the fermentation time course is highly challenging as it ultimately decreases the yield of production. This problem harms the production of challenging biopharmaceuticals the most, among these one could name FTN2. According to others, heavy chain of FTN2 is more susceptible for degradation than the light chain, but there has been no report about degradation rate or concentration of degraded content for FTN2 yet.
The aim of this doctoral study is to elaborate a general understanding of proteolysis capacity of the host cells during its production in E. coli expression systems under different conditions by using two different methodologies: application of non-canonical amino acids and monitoring the amylase activity of malS. Therefore, the project consists of two major tasks:
Task 1: Application of non-canonical amino acid for monitoring degradation of the recombinant protein
Application of non-canonical (nc) amino acids provides a site-specific label within the protein of interest which guarantees site specific conjugation of drugs and dyes, and measuring protein activity with high accuracy. In this project the aim is to make benefit of this characteristic of non-canonical amino acids to measure protein degradation.
In the first step, one amber codon should be introduced within coding sequences of Heavy- and Light-chain, in regions that do not disturb the protein activity and its translation [4, 5]. The possible positions should be determined and corresponding constructs should be tested regarding Fab production (successful translation, yield and activity). Afterwards, according to results the best construct will be used. As incorporation of amber codon may lead to reduced translation efficiency and consequently lower product yield, most efficient position should be determined among those position already determined by bioinformatic database.
In the next step, for site specific labeling of the nc-containing FTN2, azido-alkyne cycloaddition chemistry[6, 7] will be used to tag the nc-containing FTN2 with a fluorescent dye. The conjugation chemistry is not highly specific as by azido-alkyne cycloaddition reactions not only azide groups but also thiol groups will be conjugated and therefore will be the origin of background noise. This will be more challenging when small fragments are measured. Therefore, in this part, a method should be developed in a way that intensity of the background noise is at least 3 times lower than that of positive signal.
As incorporated nc could be find in intact FTN2, its chains in intact or truncated forms, short fragments and even free nc format, the important step is to set up an easy methodology to remove intact forms from the lysate. Diafiltration and L and G protein purification are two techniques that will be tested for removing intact forms to have reliable calculations. However, separation process which used for separation of captured molecules should be optimized regarding the protein loss rate that strongly affects the results specially when the concentration of the to be measured protein is low. Protein loss rate and percentage of protein conjugation using click chemistry reaction are the two challenging steps that might lead to reduction in concentration of the target molecule and ultimately make it undetectable.
Ultimately, fluorescent signal will be indication of degraded fragments presence and correlated with concentration of degraded portion of FTN2. Intensity of the fluorescent signal of degraded fragments at each time point of cultivation will determine the kinetics of FTN2 degradation. In addition, effect of different cultivation conditions on proteolysis of FTN2 or other protein of interest will be measurable.
Task 2: Monitoring the amylase activity during FTN2 production time course
To keep the cell homeostasis, proteolytic machinery of the cells degrades the unfolded proteins. When host cells are under high metabolic load, not only the unfolded but also folded protein (recombinant and even host protein) are degraded. This phenomenon leads to decrease in yield of biopharmaceutical production.
As periplasmic amylase (malS) is a direct target of degP (degrades FTN2), monitoring its activity during the fermentation time course will determine that is there any correlation between the host cell metabolic load and malS degradation or at least is malS among the first host cell priority for digestion. If there is a correlation between amylase activity and proteolytic activity of the host cell during the fermentation time course, then monitoring the amylase activity could be a useful tool for monitoring overall cell condition.
Since there is a cytoplasmic amylase (amyA), in the first step, BL21(DE3)ΔamyA strain will be used to check the feasibility of the study with malS, and then the activities of the both enzymes (malS and amyA) will be monitored using another strain under different cultivation conditions.
In case that there is a correlation between malS and protease activities, it should be checked if this correlation is valid under different cultivation conditions, metabolic load and for different host cells.
In addition, to have overall understanding of cell condition, despite amylase activity measurement, yield of FTN2 production, overall protease activity of the host cell, and transcription of malS gene will be monitored at different time points for two different cell types and under different metabolic loads.
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