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

2-D DIGE Improves Process Understanding

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

  • There are strong demands from the FDA and EMEA to assure the safety of therapeutic products. Thus, it is becoming increasingly important for biopharmaceutical manufacturers to obtain a deeper understanding of how process conditions affect the quality of the final product with regard to impurities.

    Impurities can be related to the process, product, or host cell and may include host-cell proteins (HCP), DNA, viruses, or IgG aggregates. For biopharmaceuticals manufactured using recombinant DNA technology, the majority of impurities encountered are host-cell proteins.

    Because HCP can be immunogenic and possibly cause anaphylactic reactions in patients, routine HCP determination is compulsory for all recombinant therapeutics including enzymes/proteins and hormones. ELISA is currently the standard approach for HCP determination, although it is usually performed in combination with other methods such as 1-D SDS-PAGE or IEF-PAGE to give more information about the proteins present.

    In this study we used a model system to illustrate the possibilities of using 2-D DIGE (2-D Difference Fluorescence Gel Electrophoresis) to improve the understanding of process conditions in the production of biopharmaceuticals. The 2-D DIGE method is proven to have high sensitivity and specificity, and can be used as a stand-alone method for characterization of HCP profiles without the need for antibodies.

  • HCP Profiling

    Although ELISA, Coomassie-stained SDS-PAGE, and IEF-PAGE are the methods currently used as standard for HCP determination, they each present problems with regard to HCP analysis. While immunoassays such as ELISA have the advantage of specifically detecting immunoreactive proteins, they do not detect weakly reactive proteins or non-immunoreactive proteins. Hence, the FDA is expressing concerns that these assays might not be sufficient to give a complete picture of contamination with HCP.

    Immunologic methods are not always easy to work with, as they are arduous to develop, and specific antibodies must be acquired. False negatives may be detected by antibody-based assays due to sample denaturation or steric hindrance causing epitopes to be missed, and false positives may also be detected due to cross-reactivity. In addition, although immunoassays detect the presence of immunoreactive HCP and quantify the total amount, complimentary methods are needed in order to elucidate HCP patterns.

    The HCP pattern can be observed and quantitated with 1-D SDS-PAGE or IEF-PAGE, but the quantitation level varies depending on the equipment (e.g., software) available, both resolution and sensitivity are limited, and IEF-PAGE data is difficult to correlate to SDS-PAGE data. Also, these methods lack reliable internal markers for accurate quantitation.

    2-D electrophoresis is an established method, commonly used in proteomic research for analyzing complex protein mixtures. 2-D DIGE was developed with the aim of simplifying the process and improving quantitation. 2-D DIGE is an electrophoretic method that allows accurate quantitation of small differences in protein abundance between different samples with high statistical confidence.

    The Ettan™ DIGE technology from GE Healthcare allows for the simultaneous co-separation of two different samples, plus an internal standard, on an individual gel. The samples and internal standard are each fluorescently labeled with a different CyDye™ DIGE Fluor dye. Because two samples are multiplexed using the same internal standard on each gel, and each protein spot has its own corresponding internal standard spot used for normalization, all gels can be directly compared, reducing the number of gels required for each experiment.

    In contrast to immunoassays, 2-D DIGE detects all proteins, independent of their immunogenic response. Using DeCyder™ 2-D software, 2-D DIGE can detect the smallest possible real differences in protein expression, quantitatively and with statistical certainty. These advantages address the need for quantitative and sensitive HCP profiling.



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