Week 9: Designing immunofluorescence panels and MACS

Hi guys! 

Last week, we took our reconstituted ovaries, fixed them in paraformaldehyde, washed in a wash buffer called PBST, and soaked them in a blocking buffer for a week till we got back.

On Monday, we incubated the reconstituted ovaries with the first set of primary antibodies that would bind to our antigens of interest, which are mostly fluorescent proteins like Oct4GFP, FOXL2, and VASA that help us detect the different kinds of cells in the reconstituted ovary (different stages of germ cells and somatic cells). In addition, we use stains like DAPI and Phalloidin. Also recall, the germ cells we added in to the reconstituted ovaries were oogonia, but we know that over time, they will have differentiated into becoming oocytes (oogonia that have entered meiosis).

Now, a little about what the antibodies and stains target. The anti-Oct4GFP antibody binds to the Oct4GFP, which is present in germ cells but most strongly expressed in oogonia (it is less expressed as the oogonia develops into oocytes and follicles). DAPI is a stain that targets all nuclear DNA, so it will target nearly every cell whose nucleus it can penetrate. FOXL2 is a protein expressed by pre-granulosa and granulosa cells, the cells that surround and support the oocyte. While VASA is also a germ cell marker, it is expressed by oocytes specifically (so no oogonia this time! That’s why this marker is really important for the specificity of development we are trying to observe). Finally, phalloidin stains actin, and while actin isn’t as related to observing oogenesis right now, it can certainly help us visualize the follicle morphology and structure.

Now when an antibody binds to the antigen, we can capture the signal during imaging so we can identify the location of the antigens/proteins based on where the antibody binds. The primary antibodies were added to the blocking buffer, and the next day, we washed away the blocking buffer and incubated the reconstituted ovaries in secondary antibodies. Why do we need secondary antibodies when we already have primary antibodies? A secondary antibody binds to a primary antibody. This is useful when the signal from the primary antibody isn’t strong enough, or when we are trying to be extra robust and ensure that we only capture the signals from the primary antibodies, as secondary antibodies are also highly specific. Then we put the reconstituted ovaries on a slide, added an antifade reagent which stabilizes the fluorescent signal from the proteins, and sealed the slide. (Guess what we sealed the slide with? Sally Hansen Top Coat! That’s right, only the highest quality for our reconstituted ovaries). The reconstituted ovaries once again are placed in a room that blocks out light, as light can damage the ovaries.

On Wednesday, I also got to watch a MACS sort — Magnetic Activated Cell Sorting. You might recall up till this point we have been using FACS (Fluorescence Activated Cell Sorting) to sort our germ cells from the somatic cells each time we dissociate a mouse embryonic ovary after a dissection. FACS is extremely pure as it detects the fluorescent protein our germ cells express to give a high accuracy during sorting. However, it is extremely long, and MACS is useful for “lesser-stake” experiments. In our case, we used MACS just to get some somatic cells to bank, so even if we lost oogonia along the way, it doesn’t make a big difference. MACS uses magnetic beads, and we used beads that target specific antigens found in germ cells, like SSEA-1 (Stage-Specific Embryonic Antigen). Thus, the germ cells would get stuck to the beads and the somatic cells flow through the magnetic column during sorting. With this, we were able to bank some more somatic cells, which is very helpful for the next time we want to make reconstituted ovaries!

I also genotyped another mouse litter, imaged the gel, and got to make a few more visits to the mouse house!

On the computational side of things, I am still working on the CellChat analysis from last week. Additionally, some of the code from our pySCENIC analysis took too much RAM to perform before so we are troubleshooting and finding a way to use the UCSF cluster to perform the job!

Thank you for joining me! See you next week.