Abstract
Capillary isoelectric focusing is a useful analytical technique for characterization of protein mixtures and determination of protein isoelectric points. It is particularly useful in separation of protein glycoforms (Fig. 5), characterizing protein microheterogeneity (Fig. 6), and resolution of charge variants (Fig. 7). The capillary focusing process is analogous to conventional isoelectric focusing in gels, while the requirement for zone mobilization is unique to the capillary format with on-tube detection. A variety of mobilization methods have been described, and the selection of the mobilization method for a particular application depends on the capillary type, the instrument configuration, and the type of proteins to be analyzed. Capillary IEF is generally successful for proteins with a molecular weight up to about 150,000 that exhibit good solubility in aqueous buffers, but may be unsatisfactory for large or hydrophobic proteins. Because of precipitation and variation in mobilization efficiencies, use of internal standards is recommended in most applications. Capillary IEF can be compared to conventional gel IEF in terms of sample throughput and sensitivity. Conventional gels require approximately 4-6 hr to cast, run, and stain the gel, depending on whether silver or Coomassie staining is used. A typical gel contains 10 sample lanes, yielding a throughput of 25-35 min/sample. Capillary IEF separations (including focusing and mobilization) are typically 15-20 min. The mass sensitivity of conventional gel IEF is 36-47 ng for Coomassie staining and 0.5-1.2 ng for silver staining. In capillary IEF, sensitivity will depend on the volume of sample injected; assuming a capillary with a volume of 100 nl is completely filled with sample prior to focusing, the limit of detection will be approximately 1 microgram/ml or 0.1 ng injected. Thus capillary IEF compares favorably with conventional gel IEF in terms of detectivity and analysis time, and has the additional benefit of complete automation of the process including separation and data reduction.
Collapse