The expression patterns of surface antigens are associated with the differentiation status and functional characteristics of mammalian cells. To analyze the surface antigen expression pattern in a high-throughput manner, antibody microarrays have been developed by several groups, including ours. This analysis can be performed using cell-binding assays on microarrays; moreover, this approach has advantages over conventional flow cytometry (FCM). Unlike FCM, the microarray-based method cannot evaluate the concurrent expression of more than two surface antigens on a single cell, and therefore, it cannot be used for cell subset analysis. To overcome this drawback, we prepared an antibody microarray with spots presenting co-immobilized multiple antibodies together with spots presenting each antibody separately. The co-immobilized spots are expected to be reactive for every surface antigen specific to the co-immobilized antibodies. In addition, the concept of an algebra of sets is incorporated into the derivation of quantitative data regarding cell subsets. Here, taking cell subsets with respect to two surface antigens as the simplest example, antibody microarrays were prepared and initially subjected to validation studies to verify the accuracy of cell-binding assays. Quantitative subset analysis was performed using antibody microarrays prepared using the anti-CD13 and anti-CD49f antibodies. For model populations that consisted of discrete subsets, THP-1, HL-60, CCRF-CEM, and Ramos cell lines were used because they were found by FCM to have a singular phenotype, that is, CD13+CD49f+, CD13+CD49f-, CD13-CD49f+, and CD13-CD49f-, respectively. Five populations were prepared by mixing these cells at various ratios and analyzed for their subsets using microarrays. The results showed that the experimentally determined abundance ratios of the four model subsets were in good agreement with the predetermined abundance ratios, which provided the proof of principle for the new method in the quantitative subset analysis.
Keywords: Venn diagram; algebra of sets; antibody; flow cytometry; high-throughput analysis; subset; surface antigen; surface marker.