Image Cytometry: A powerful tool for the study of sickle cell disease. — Australasian Cytometry Society

Image Cytometry: A powerful tool for the study of sickle cell disease. (24089)

David Archer 1
  1. Emory University, Atlanta, GA, United States

Polymerization of deoxygenated hemoglobin and the subsequent formation of sickled red blood cell morphology remain central to the pathophysiology of sickle cell disease (SCD). Human peripheral blood samples from patients with sickle cell disease were collected via the sickle cell biorepository under an IRB approved protocol. In vitro O2 equilibrium curves were generated on a Hemox instrument.  While generating the O2 equilibrium curve, consecutive aliquots of 50 ul of sample were collected at known pO2 values. The cell suspensions were immediately fixed, washed, permeabilized with 0.1% TX-100 for 10 min, and incubated with pre-conjugated antibodies.  Labeled cells were analyzed by image flow cytometry (Amnis ImageStreamX MkII). Due to the variation of sickled RBC morphology, there isn’t a single built-in or customer-made feature that can separate sickled cells from normal cells. To automate the quantification of percent sickling, we used sequential approaches that gradually identify normal RBCs from sickled cells.

Circularity and shape Ratio are the two strongest morphometric features that separated normal and sickle cells. We used a sequential approach to further separate normal cells from sickle cells until all cells were distributed to sickle or normal cell populations.  We verified the algorithm by hand counting in multiple in vitro sickling assays. We have developed an algorithm that can automatically quantify the percentage sickle cells in peripheral blood samples and that this can be combined with immunolabeling to further investigate RBC biology and the process of sickling.

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