Novel analytical pipeline reduces spectral flow cytometry errors up to 9000-fold

Pre-print alert! And this one really is a must read for anyone that does spectral flow cytometry. It is a complete, fully-automated spectral unmixing pipeline that reduces error up to 9000-fold, created by our cytometry guru Oliver Burton, of Colibri Cytometry fame.

We've all seen the problems - spreading, skewing, autofluorescence intrusion. Unmixing errors are so ubiquitous in high parameter panels they are often thought of as unavoidable, intrinsic to the way the hardware works. Surprisingly, they are largely artefacts of the unmixing software being used.

The problem is that spectral unmixing is complex. The basis is a linear regression of positive versus negative signals, a highly error-prone process. This issue is largely solved by the use of robust linear regression with iterative rounds of improvement (which we pioneered with AutoSpill). However there are three additional problems, which become bigger the more fluorophores are used:

1)This unmixing solution still requires ideal positive-negative matching to find the right linear regression. This isn’t trivial, as the cells positive for one marker might have completely different autofluoroscence profiles to the cells positive for another marker. Using the same negative population gives you spillover calculation errors.

2) Cells have variation in background fluorescence. An unmixing matrix that doesn't account for autofluorescence will force all signal into one of the flurophore channels, giving misassigned signal. Past approaches only use a single autofuorescence index, which means heterogenous mixtures have cells with misassigned signal.

3) Fluorophores actually stuck on cells have variation in emissions, and using only a single profile will lead to misassigned signal on some cells.

Some of these problems can be tackled (partially) by a highly skilled flow cytometrist, willing to spend days on each unmixing matrix, manually selecting populations for positive and negative cells and running multiple sets of calculations depending on which markers they want to assess. AutoSpectral does it all in a completely automated pipeline, using a robust statistical model that is highly reproducible and visibly reduces the error.

For positive-negative calculations, intrusive events are purged and scatter-matching is used to identify the suitable negative population for each positive population. We then use robust linear regression with iterative improvement to find the ideal unmixing matrix.

We can also deal with heterogeneity in the cells by identifying all autofluorescence patterns in the unstained sample, then applying each pattern to each individual cell in the real sample. We select the autofluorescence index that leaves the least residual, subtract that signal and unmix the rest.

The same is true for fluorophore variation - we can test the different fits on a per cell basis, and use the fit that leaves the least residual. It means more signal is attributed to the correct fluorophore.

 

The cumulative effect of these improvements is enormous. For tough samples, like lung, incorrectly assigned signals are reduced by up to 9000-fold, and a 10- to 3000-fold improvement is common. We demonstrate the improvement in synthetic experiments with known ground truth, and multiple real-world complex panels, where we can use known biology to see the improvements. For example, look at this experiment, where the wildtype has no GFP signal and the GFP transgenic should have GFP in CD4 and CD8 T cells. Since this sample is from the lung, the autofluorescence of macrophages gives a huge GFP signal in the wildtype mouse, which completely confounds the genuine GFP signal in T cells. Switching over to AutoSpectral, and exactly the same samples, with exactly the same cells, behave just as you would expect, little signal in the wildtype and a CD4+ and CD4- population in the GFP transgenic.

The whole pipeline is available right now on GitHub. Don't be intimidated by R, it includes comprehensive notes on every step from installation to utilisation, and only takes a couple of minutes to run per experiment. Hopefully soon (like with AutoSpill) it becomes standard on commercial platforms too.

Full article is available here.

Optimisation of blocking during flow cytometry

Another new flow cytometery guide drop from Oliver Burton, just published in Current Protocols.

This one is on optimising blocking while preserving signal, in particular how to overcome Fc interactions and dye-dye interactions, and preventing tandem break-down.

The details are in the protocol, with variants for intracellluar and cytokine staining, but generally-speaking normal mouse/rat serum, BioLegend Tandem stabilizer and Thermo/BD Brilliant Stain Buffer is an optimal combo. True-Stain and other additions aren't worth the extra $$$.

For Tandem Signal Enhancers, you don't really need them for mouse cells, and for human cells a cheaper alternative is simply to fix your cells and stain with tandems after fixation. Both eliminates non-specific tandem binding and also reduces tandem break-down. Since monocyte blocks reduce transcription factor detection, for some reason, leave them out if you are doing intracellular staining.

 

The Brilliant and Super Bright dyes really do need the Brilliant Stain buffers, but be aware that these buffers are mildly fluorescent, so leave them out if you don't need the dye, and titrate them down when you use them. 1/2 to 1/4 is normally good, and for many antibodies even lower is fine (and cheaper!).

For the tandem dyes, Tandem Stabilizer is good, but you can make it easier through panel design. Tandem breakdown is not purely chemical - it is higher on monocytes than lymphocytes, and is largely abolished in fixed cells. So move those tandem dyes to post-fix T cells if you can!

 

We've tried to cover all the main use cases, so take a look at Oliver's trouble-shooting guide to reduce off-target binding and preserve signal.

A near-universal ultra-cheap fix/perm protocol for flow cytometry

For our flow cytometry peeps, would you like to have a single fix/perm protocol that is optimised for everything? One that preserves fluorophores while allowing simultaneous TF and cytokine staining? How about a protocol that is 100-fold cheaper than your current one?

Over the last 8 years, Oliver Burton has tested >1000 different fix/perm combos, and here the final verdict is: "Burton's Best Buffer": 2% formalin, 0.05% Fairy dish soap, 0.5% Tween-20, 0.1% Triton X-100.

Yep, replace all of those expensive detergents with Fairy dishwashing liquid. It is as good as the BD Foxp3 fix/perm kit for transcription factors, as good as eBio perm for cytokines, preserves even weak endogenous GFP killed by most fix/perm combos, and preserves dye integrity too. Burton's Best Buffer is simply the best fix/perm protocol to use under any condition (except phospho-flow).

Plus it is dirt cheap - one bottle of Fairy (or Dreft, Dawn, Yes, JAR, or whatever they sell it as locally) will literally last your lab for decades.

Take a read of the protocol here.

Overnight staining of flow cytometry samples │ Oliver Burton