Identification and Analysis of Mouse Erythroid Progenitors using the CD71/TER119 Flow-cytometric Assay

The overall goal of the following experiment is to identify red cell precursors directly in freshly harvested tissue in mice. This allows us to study their molecular properties during times when the erythropoietic system in these mice is undergoing change. For example, during embryonic development or during the response to hypoxic stress, first hematopoietic tissue is isolated from mouse fetal liver or adult spleen or bone marrow and dissociated into a single cell suspension.

Next cells are labeled with antibodies against the cell surface markers CD 71 and TER one 19, and with any other markers of interest, for example, to measure cell survival or cell cycle status, the labeled cell suspension is then analyzed using a flow cytometry analyzer and specific erythroblast subsets at distinct stages of maturation are identified. These specific subsets may be purified by cell sorting. Subsequently, cellular and molecular analysis may be carried out for each erythroblast maturation subset.

The ability to identify erythroblast at specific maturation stages directly in freshly isolated hematopoietic tissues gives us the opportunity to study the cells in the physiological cortex. This method therefore allows us to study high erythroblasts of different maturation stages, respond in vivo. When mice is subjected to stimuli, they accelerate the erythropoietic crate.

For example, hypoxic conditions that mimic high altitude or injection of the hormone erythropoietin. We use multi-parameter flow cytometry to identify a blats within a complex tissue environment and simultaneously study their signaling survival and cell cycle status. We can also sort erythroblasts its specific maturation stages directly from fresh tissue and explore their gene expression levels, chromatin status, or other molecular functions.

Mouse definitive erythropoiesis takes place in the spleen and bone marrow of the adult mouse. Therefore, these tissues will be harvested from a euthanized mouse. After euthanizing the mouse draw blood by cardiac puncture into EDTA or heparin blood collection tubes, this blood will be used later for hematocrit count, reticulocyte count or CBC analysis.

Place the harvested spleen and femur in separate tubes containing cold staining.Buffer. Keep harvested tissues on ice if desired. Weigh the spleen.

Mice undergoing an erythropoietic stress response are likely to show a significant increase in spleen weight. Subsequently, spleen cells and bone marrow cells are prepared from the harvested tissues by procedures demonstrated previously in the mouse embryo. Definitive erythropoiesis takes place in the fetal liver between embryonic days 12.5 and 15.5.

Timed pregnant female mice are prepared for obtaining fetal liver cells on days 12.5 to 14.5 of pregnancy. The timed pregnant female mice are euthanized and the uterine horns are removed into a Petri dish containing ice. Cold culture medium or staining buffer.

A dissecting microscope is required for dissecting fetal liver from embryonic day 12.5 or younger to remove embryos from the uterus. First separate each bead away from the horn. Then gently excise the wall of the uterus to release the embryo that is within its amniotic sac.

Gently peel off the amniotic membrane. The fetal liver is the largest red abdominal tissue located underneath a much smaller heart. To dissect the fetal liver, use forceps to immobilize the embryo on either side of the liver and gently push the liver out of the abdomen into the medium.

Gently transferred the liver to a tube containing fresh staining buffer. After all fetal livers have been dissected and transferred to a tube containing fresh staining. Buffer dissociate the livers mechanically by pipetting, then filter the dissociated cells through a 40 micron nylon mesh screen wash cells twice by centrifugation, discarding the supernatant and resus suspending in staining buffer.

After the second wash, stain cells with trian blue and count using a hemo cytometer. A fetal liver at E 13.5 has around 10 to the seventh. Cells resuspend the cells at one to two times 10 to the sixth cells per 200 microliter sample for flow cytometric analysis.

For the purposes of this video protocol antibody staining for flow cytometry will be demonstrated on only the fetal liver cells. To begin this procedure, prepare a primary antibody staining premix containing the following, purified rabbit IgG for blocking FC receptors in mouse cells CD 71 FETR one 19 PE and an antibody directed at the cell surface protein fast. Mix the antibody solution gently by inverting the tube two to three times add 200 microliters of the primary antibody staining pre-mixed to the previously prepared fetal liver cell sample and pipette up and down gently to resuspend the cells.

Next, prepare these six control cell samples. An unstained sample in which cells are left in staining buffer to provide the background autofluorescence of the cells, a single color for each antibody or color used in the protocol to correct for spectral overlap between channels, which in this experiment are TUR one 19 PE CD 71 fz fast, biotin and streptavidin A PC and seven A A DA fluorescence minus one control for fast biotin, which provides the true background for that channel where the cells are stained with all the colors or antibodies in the protocol except for fast biotin. Incubate the sample and relevant controls in the primary antibody stain on ice for 45 minutes to one hour in the dark.

At the end of the incubation, wash the cells by adding three milliliters of staining buffer to each sample tube and spin for three to five minutes at approximately 400 times gravity at four degrees celsius. Next, apply the strep avid in a PC and incubate the tubes on ice for 30 to 45 minutes. At the completion of the incubation, wash the cells as for the first antibody stain.

Finally, resuspend cells in staining solution containing the cell impermeable, DNA dye seven a a d to exclude dead cells. The samples are now ready for flow cytometry analysis. The most difficult aspect of this procedure is correct gating analysis of flow cytometric events allowing reliable identification of erythroblast subsets.

It requires careful machine set up all the correct control samples, careful compensation for spectral overlap and subsequent gating that excludes dead cells, aggregates, and very small events. At the start of data analysis. The unstained sample and the single color control samples are used to set up the compensation for spectral overlap for each color combination.

In this example, we will show how fit e fluorescence spills into the PE channel and how this spectral overlap is corrected After compensation. First, using the unstained control, we define a fit E positive and PE negative region. Next, using the fit E single color control, we can visualize the spectral spillover into the PE channel.

Following digital compensation with the FlowJo software, the spillover fit E signal in the PE channel is minimized. Once compensated dead cells, aggregates and small events can be removed. Aggregates and cell doublets are removed by plotting forward scatter height versus forward scatter area and selecting for events within a narrow diagonal gate.

Dead cells are removed by selecting cells that are negative for dapi A cell impermeable DNA die. The DAPI negative viable cell gate also excludes very small events such as nuclei or debris, which have a very low forward scatter. Next, we will show the gating strategy for fetal liver cells.

Freshly harvested cells were labeled for CD 71 TUR one 19, and a cocktail of ZI labeled antibodies directed at non erythroid lineage markers. In this example, samples have already been compensated for spectral overlap and then gated to exclude aggregates dead cells and very small events. We use the FMO sample that contains all colors except for the lineage positive fitzy stain to plot a fitzy histogram and define the lineage negative cell gate, we next apply this gate to the fetal liver cell sample that was stained with ZI conjugated lineage markers.

Lineage negative cells are selected and plotted with CD 71 on the Y axis and TER one 19. On the A axis, cells are now ready to be divided into subsets S zero to S five. The Lin depleted S zero subset largely contains cells with CFUE potential prior to the onset of EPO dependence.

The S one subset contains EPO dependent CFUE cells largely in S-phase of the cell cycle. S two subset cells have lost colony forming potential and are beginning to express hemoglobin S3 subset cells are largely basophilic Erythroblasts S four and S five subsets contain late erythroblasts. Shown here is the analysis strategy following the data acquisition from spleen cells processed and labeled with antibodies directed at CD 71 and TER one 19, as well as the death receptor fast histogram.

One shows all acquired events where the diagonal gate represents events that are likely to be single cells, excluding doublets or larger aggregates. Cells in this gate are further analyzed in histogram two here. Very small events likely nuclei or debris are excluded.

The gated cells are shown in histogram three where DAPI positive cells that are likely membrane permeable apoptotic cells are excluded from further analysis. Histogram four shows the resulting population of viable spleen cells. The pro eGate contains CD 71 high TER one 19 Intermediate cells tur R one 19 high cells are further analyzed in histogram five.

Here, CD 71 high cells are subdivided into less mature large area, a erythroblasts and smaller, more mature A B erythroblasts. The most mature erythroblast subset is ARI C.Expression of cell surface proteins may be measured simultaneously for each of these subsets by adding the relevant antibodies at the same time as TER R one 19 and CD 71. Staining histogram six shows cell surface expression of the death receptor fast, specifically in the area, A subset in mice in the basal state and mice injected with a single dose of E ppo.

The results indicate that EPO suppresses fast expression in the area. A population in vivo expression of intracellular proteins or cell cycle status may also be measured for cells in each subset. In this representative cell cycle analysis, mice were injected intraperitoneal with BRDU and bone marrow was harvested 30 to 60 minutes later.

In addition to being stained for CD 71 and TER one 19, cells were stained for BRDU incorporation into their replicating D-N-A-B-R-D-U positive cells are in S-phase of the cycle. Interface cells are BRDU negative and may be resolved into G one or G two M phases. Using the DNAD seven A A D cells may be sorted from each of the PRO E area A A B and A EC subsets.

Here they are shown in cytosine preparations showing sequential maturation with decreasing cell size nuclear condensation and increasing brown coloration reflecting hemoglobin expression. Finally, a representative cell cycle analysis of the S3 subset in E 13.5 fetal liver is shown here. Pregnant mice were injected with BRDU.

Fetal livers were harvested 30 to 60 minutes later fixed perme and stained with antibodies against CD 71, TER one 19 and BRDU. The cell cycle status of S3 cells is analyzed where S-phase cells are. BRDU positive and DNA content is quantified by staining for the DNA dye seven A a d.

The cytometric approach we describe allows simultaneous investigation of cellular functions such as expression of cell surface markers and other proteins, cell survival cell signaling using fosso specific antibodies and cell cycle status. It therefore allow us to investigate the molecular responses of erythroblasts, a different maturation stage to a wide range of stimuli or the effect of genetic mutations. It should be noted that the flow cytometric maturation subsets are defined in terms of cell surface marker expression and forward scatter.

We found that in general, cells in each subset correspond to similar morphological erythroblast stage in a wide variety of mouse models. However, we recommend verifying this when examining a new mouse model. By sorting cells from each subset and examining their morphology Cells from each subset can also be sorted for RNA or transcriptome analysis sort experiments use low sorting pressures and wide noses in order to minimize the sheer stress on the cells.

We also recommend checking cell purity and viability following each sorting experiment. Finally, when detecting a change in the frequency of a given subset, it is important to determine whether this is due to a true change in the number of cells in that subset or whether it is due to changes in other subsets. Therefore, in addition to measuring subset frequencies, it is always necessary to also measure the absolute number of cells in each subset.