Imaging flow cytometry for the study of erythroid cell biology and pathology

Abstract

Erythroid cell maturation and diseases affecting erythrocytes are frequently accompanied by morphologic and immunophenotypic changes to these cells. In the past, these changes have been assessed primarily through the use of manual microscopy, which substantially limits the statistical rigor, throughput, and objectivity of these studies. Imaging flow cytometry provides a technology to examine both the morphology of cells as well as to quantify the staining intensity and signal distribution of numerous fluorescent markers on a cell-by-cell basis with high throughput in a statistically robust manner, and thus is ideally suited to studying erythroid cell biology. To date imaging flow cytometry has been used to study erythrocytes in three areas: 1) erythroid cell maturation, 2) sickle cell disease, and 3) infectious diseases such as malaria. In the maturation studies, imaging flow cytometry can closely recapitulate known stages of maturation and has led to the identification of a new population of erythroid cell precursors. In sickle cell disease, imaging flow cytometry provides a robust method to quantify sickled erythrocytes and to identify cellular aggregates linked to morbidities, and in malaria, imaging flow cytometry has been used to screen for new chemotherapeutic agents. These studies have demonstrated the value of imaging flow cytometry for investigations of erythrocyte biology and pathology.

Spherocytic shift of red blood cells during storage provides a quantitative whole cell–based marker of the storage lesion

“…Because fine morphologic classification of RBCs depends on the pH and composition of the suspension medium we used Krebs‐albumin solution shown in preliminary experiments to provide the best preservation of surface area including the bimodal distribution of stored RBCs, compared to serum or plasma. Imaging flow cytometry has been increasingly used to study RBC morphology and pathology . Although it generates less precisely defined images than does conventional microscopy, the analysis of critical size and shape features on many unfixed RBCs using the IDEAS postacquisition software is rapid, objective, and reproducible.…”

Exploiting single-cell quantitative data to map genetic variants having probabilistic effects

“…This requirement also implies using technologies where the throughput of quantitative acquisitions is high. This is the case for flow-cytometry and, although at higher costs, for high-content image analysis [15,16] and digital microfluidics [18,19]. For these practical reasons, it is possible that mouse immunological studies will help making progress in mammalian scPTL mapping.…”

“…Technological developments in high-throughput flow cytometry [13], multiplexed mass-cytometry [14], image content analysis [15][16][17] and droplet-based single-cell transcriptome profiling [18,19] now offer the possibility to estimate empirically the statistical distribution of numerous molecular and cellular single-cell quantitative traits. We therefore propose to scan genomes for variants that modify single-cell traits in a probabilistic manner, which we call single-cell Probabilistic Trait Loci (scPTL).…”

Applications of imaging flow cytometry in the diagnostic assessment of red cell membrane disorders

“…IFC combines microscopy and flow cytometry features by capturing microscopic illumination and fluorescent images of large number of cells, which can be quantified for both morphometric and fluorescent characteristics. Since last 10 years, this approach has been increasingly used to study aspects of red cell morphology (Samsel et al, ) and has been used in many hematological studies such as erythroid cell biology (Samsel & McCoy, ), in the megakaryocyte cell biology and pathology (Niswander, McGrath, Kennedy, & Palis, ), also in the assessment of projected surface area, volume and morphological changes in the stored red blood cells in the blood bank (Roussel et al, ). This method is also used in the study of the intracellular pathogen (Haridas, Ranjbar, Vorobjev, Goldfeld, & Barteneva, ).…”