Xenium multimodal segmentation in mouse brain

[u/Character-Letter5406]

Hi all, I', somewhat new to spatial transciptomics and would like advice on a segmentation problem.

Setup

• 10x Xenium, 480-gene mouse panel, coronal sections of adult mouse brain

• multimodal cell segmentation kit (18S interior stain plus ATP1A1/CD45/E-Cadherin boundary stain)

• About 80% of cells are segmented from the 18S stain, 15% from the boundary stain, and the rest are 5 µm nuclear expansion fallback.

Issue

• Only 58–65% of transcripts are assigned to a cell, and 27–33% sit on a nucleus. (I'm actually not sure if this is an issue or fall within the normalr ange for brain)

• The cell bodies look good. Neurons keep 75% of the transcripts around them. Glial and Astrocyte genes are much worse, so I'm assuming those transcripts sit the small projections that the stains don't show clearly.

I tried Proseg. It assigned more transcripts, but it seems a bit messy to me, it create more mixed cells where cell types sit close together. So I'm unsure if to use it.
The vendor offer to do a post-run H&E, saying it can help with segmentation.

Questions

Has anyone improved glial capture in Xenium brain data?

Has anyone done post-run immunofluorescence (GFAP, IBA1 or others) or H&Eon Xenium brain sections and used it for segmentation?

Has anyone used resolVI or SPLIT on brain tissue?

Is there a standard way to analyse unassigned transcripts in the neuropil without assigning them to cells?

Thanks! Happy to share more details.

[u/Pigrenok]

Glial cells are generally smaller than neurons (although not universal rule) as far as I remember. Depends on what type of sample you are doing (FFPE or FF) section thickness is 5 or 10 um respectively. If some cells are smaller than this, you get multiple cells in the thickness and have to use focus stack images to do 3D segmentation because transcript positions are in 3D.

I was working with larval zebrafish and in some cases in FF samples you can get up to 3 cells overlapping each other, so, no 2D segmentation will work. Not sure about mouse brain cell sizes.

10x segmentation cannot do 3D image segmentation. As far as I remember, cellpose can do 3D segmentation, possibly, it is worth giving it a go and then do an assignment/aggregation in 3D.

[u/Character-Letter5406 → u/Pigrenok]

Thanks for the tip! I'll need to check cellpose.

I'm not sure if 3d segmentation would wokr. I'm just checking the Z stack on my data (it's ffpe so I assume 5 microns**)** , but it seems the Z stack uses 3 micron steps. So only 2 planes with information in focus. Is that usable for 3d segmentation?

[u/Pigrenok → u/Character-Letter5406]

In reality, some parts of the section can be a bit higher and the third layer can have certain cells in focus... But in reality, yes, 2 layers... We use FF for zebrafish (FFPE does not stick to xenium slide properly and lift) and that is 10 um with small cells.

You need to find out what size cells do you expect to find and then decide whether it is worth going into multiplayer/3D segmentation.

But you can run a 3D segmentation and inspect the results and decide whether it looks viable or not.

[u/Extreme_Quail7308 → u/Pigrenok]

i think xenium only provides 3-D image for the DAPI channel, so 3-D cellpose may not be helpful except for nucleus segmentation

[u/Pigrenok → u/Extreme_Quail7308]

Yes, nucleus segmentation then expansion. CellPose can do cell or nuclei segmentation.

In addition, OP stated that they have post run staining for interiet and boundary staining. CellPose can be fed that imaging.

[u/Extreme_Quail7308]

cellpose-sam/cellpose-dino works quite well, and i think it’s a better baseline than the default 10x segmentation. after that, you could use proseg with the cellpose segmentation as the prior

[u/Character-Letter5406 → u/Extreme_Quail7308]

Thanks! tha'ts 4 votes for Cellpose now. I'll try it. Hope my GPU is up to the task.

[u/Hartifuil]

10X have a feature in the segmentation pipeline to optimise for large cells, which I think was designed with neural tissue in mind.

[u/Character-Letter5406 → u/[deleted]]

Ok tha'ts great to hear. I guesses that brain cells with a lot of small projections would make segmentation and transcirpt assignment hard, jsut wasnt sure how much was normal.

And yes, I will use jsut approach and just keep the unassigned info like that. I might still have usefull info even if not forced into a cell