Unsupervised Discovery of Early Markers of Erythroid Maturation in Human Donor Marrow
Authors: Ng David P , Wood Brent 
Published: October 2019

Abstract
Antigenic expression during erythroid maturation is not well understood. Despite the large number of surface antigens currently described for leukocytes, only a few (e.g. CD36, CD45, CD71, CD117, and CD235a) have been well characterized on erythroid cells. Here, we apply novel bioinformatic tools to select antigens with high potential for identifying successive stages of erythroid maturation in an unsupervised and unbiased manner from a high dimensional dataset. In brief, flow cytometry was performed on 3 normal donor bone marrows using Becton-Dickinson lyoplates containing a total of 275 unique antibodies and 8 gating reagents (CD15, CD19, CD34, CD38, CD45, CD71, CD117, and CD123). Each of the 275 independent data files from the same donor was aligned using the gating reagents and a weighted nearest neighbor algorithm in order to synthesize a flow data set with 283 antigens and 50,000 events. We applied a modified SPADE algorithm to generate a maturational path for cells of the erythroid lineage starting with CD34+/CD38- progenitors through the mature erythrocyte stage. A non-parametric Kruskal–Wallis test was used to identify and rank antigens that show differential expression along the erythroid maturational sequence.
To discern antigens having the greatest discrimination for early vs. late erythroid maturation, we identified 15 antigens common to the top 25 most differentially expressed antigens from each donor sample. As expected, our method correctly identified the three erythroid gating reagents (CD45, CD71 and CD117) as well as previously a previously described erythroid associated antigen (CD36). A few of the identified antigens have been described are less common but also known to be differentially expressed on erythroid cells (e.g. integrin members CD29, CD44, and CD49d), however several additional novel antigens were also identified with strong differential expression including CD46, CD58, CD81, CD98, CD99, CD164, CD220 and CD321 (Figure 1). Of note, CD49d, CD98 and CD164 are of particular interest as they appear to be gradually lost during maturation from the early normoblast through the mature erythrocyte stages. This is in contrast with the other antigens that show high expression on pronormoblasts—with rapid decline during the early normoblast stage to the level of erythrocytes. We examined selected antigens from the synthetic data of all 3 samples using manual gating, and interestingly CD99 retained expression among the erythroid cells to late stage normoblasts in 2 of the 3 samples, suggesting some element of phenotypic variability among normal individuals for this antigen.
Additionally, several antigens appear useful in distinguishing erythroid lineage cells from non-erythroid precursors including beta-2 microglobulin, CD50, and HLA-ABC which all showed ubiquitous expression in non-erythroid precursors with low to absent expression among cells of the erythroid lineage.
In summary, using a novel unbiased method for large-scale antigen discovery, we have identified multiple novel antigens that are differentially down regulated with progressive erythroid maturation and appear useful in further delineating erythroid progenitor maturation. Additional work is underway to correlate these antigens with our morphologic understanding of erythroid maturation. Further work in characterizing these changes in myeloid stem cell disorders is on going and may be of diagnostic utility in the diagnosis of myelodysplastic syndromes.
Figure 1 [Red=High Expression, Blue=Low Expression] Figure 1. [Red=High Expression, Blue=Low Expression]

Disclosures
No relevant conflicts of interest to declare.