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June 15, 2009 (Vol. 29, No. 12)

2-D DIGE Improves Process Understanding

New Methodology Can Be Used to Facilitate Host-Cell Protein Determination

  • Reduction of Impurities

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    Figure 1. Improved bioprocess understanding leads to better process control.

    Identification and quantification of impurities early in the drug development process is crucial, and an improper investigation of this can lead to serious consequences. Therefore, it is important to investigate manufacturability at an early stage in the process by varying upstream conditions and analyzing the effects on downstream processing (i.e., purification). As shown in Figure 1 there are several upstream conditions (e.g., cell cloning and growth conditions) that may have quantitative and qualitative effects on HCP content in the final product.

    In controlled experiments, upstream conditions can be modified, and the downstream effects on critical impurities can be measured. By analyzing the proteome, upstream conditions can be altered to optimize bioprocessing and predict the yield and purity of the target protein. This type of analysis could also be performed on the transcriptome or peptidome to gain an even deeper understanding about the effects of a process change. Using a systematic approach, the acquired knowledge can be used to control bioprocessing on an entirely new level.

  • Selecting Optimal Conditions

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    Figure 2. A model system using E. coli cells expressing His-GFP was used. IPTG induction was performed on the cultures at two different temperatures, and the differences were analyzed.

    We cultured E. coli cells expressing histidine-tagged green fluorescent protein (GFP) at 37°C. Some of these samples were cooled to 20°C before IPTG induction and then cultured at 20°C to test different upstream conditions. After induction, six biological replicate samples were taken at each time point and temperature (Figure 2).

    Analysis using 2-D DIGE was performed on the samples, and the resulting 2-D protein spot maps of different gels were compared to the internal standard with DeCyder 2-D software. A t-test between the two temperatures showed 438 differentially expressed proteins (0.0001 level of significance). Of these, 130 proteins of interest were picked and identified.

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    Figure 3. DeCyder 2-D software analysis shows the principal component analysis plot where data from 37°C cultures (circled in red) is compared to induction at 20°C (circled in blue).

    The majority of proteins differentially expressed in E. coli were downregulated at 20°C, possibly due to stress induced by reducing the temperature after culturing. At 37°C, most of the proteins were upregulated over time. The samples taken at 20°C and time point t4 showed similarities to those taken at the early time point and 37°C (Figure 3). A possible explanation for this is that the cultures had adapted to the low temperature and started to produce similar proteins to the 37°C cultures.

    Different downstream processing conditions were analyzed by fractionating the collected samples and using either a Capto™ Q anion exchange column or a HisTrap™ IMAC HP column. Different fractions were collected from each column and analyzed by 2-D DIGE. Chromatograms from the two purification methods are shown in Figure 4A. Two examples of protein spot maps of samples cultured at 37°C and fractionated using either ion exchange or affinity chromatography are shown in Figure 4B.

    Because all gels in the experiment used the same internal standard, it was possible to link the spot maps of the fractionated samples back to the spot maps of the start material (cultured at 37°C or 20°C). The spot maps showed that several host-cell proteins were still present after IMAC purification. These were likely to be histidine- or tryptophan-containing proteins, which can also bind to the resin. Many variants/isoforms of the histidine-tagged target protein could also be separated and identified. Using information obtained from 2-D DIGE it is possible to reduce certain impurities in the eluate by selecting optimal upstream and downstream conditions.

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    Figure 4. Downstream processing is analyzed by 2-D DIGE.

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