Iterative immunostaining combined with expansion microscopy and image processing reveals nanoscopic network organization of nuclear lamina
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Abstract
Iterative indirect immunofluorescence staining (IT-IF) for expansion and structured illumination microscopy improves superresolution imaging of subnuclear nanostructures. The IT-IF increases antibody labeling density resulting in high intensity, while maintaining the signal-to-background ratio. Together with the robust denoising pipeline, IT-IF reveals the fine structural network of nuclear lamins.
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It looks like each iteration involves permeabilization. How necessary is this step in each iteration rather than simply rounds of primary and secondary antibodies with washes in between?
Also we’ve found detection of actin with fluorescent phalloidin to require improved signal and reduced background, particularly in photosynthetic cells with a great deal of chlorophyll autofluorescence. This requires 1) low concentrations, 2) reduced incubation time, and 3) brighter fluorophore such as Atto compared to Alexa dyes. For your antibodies, you mention low concentrations also result in low signal, so this is suboptimal so I’m still wondering if we could improve phalloidin staining for difficult samples with iteration. I know you don’t find similar improvements in phalloidin staining with iteration but I’m wondering if your phalloidin staining …
It looks like each iteration involves permeabilization. How necessary is this step in each iteration rather than simply rounds of primary and secondary antibodies with washes in between?
Also we’ve found detection of actin with fluorescent phalloidin to require improved signal and reduced background, particularly in photosynthetic cells with a great deal of chlorophyll autofluorescence. This requires 1) low concentrations, 2) reduced incubation time, and 3) brighter fluorophore such as Atto compared to Alexa dyes. For your antibodies, you mention low concentrations also result in low signal, so this is suboptimal so I’m still wondering if we could improve phalloidin staining for difficult samples with iteration. I know you don’t find similar improvements in phalloidin staining with iteration but I’m wondering if your phalloidin staining protocol had been optimized as much as you’ve optimized the antibody concentrations for your 1X designations to minimize signal to noise before performing phalloidin iterations to increase signal. Further, it could be that the absolute target abundance matters for the changes in signal to noise ratio with iteration. So by comparing iteration for low abundance antibody targets with iteration for high abundance non-antibody labeling, you may not see comparable improvements for a non-antibody label. If you were to use this protocol on cells where the f-actin signal is harder to detect than in these cells, might you see improvements with iterative labeling? Or alternatively if you compared antibody iteration with a non-antibody label against a target of lower abundance in the same cells, perhaps the signal to noise difference would change more with iteration? It would be of general interest if iterative staining could also improve signal to noise for low signal or low abundance non-antibody labels.
Thanks for publishing this interesting study!
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It looks like each iteration involves permeabilization. How necessary is this step in each iteration rather than simply rounds of primary and secondary antibodies with washes in between?
Also we’ve found detection of actin with fluorescent phalloidin to require improved signal and reduced background, particularly in photosynthetic cells with a great deal of chlorophyll autofluorescence. This requires 1) low concentrations, 2) reduced incubation time, and 3) brighter fluorophore such as Atto compared to Alexa dyes. For your antibodies, you mention low concentrations also result in low signal, so this is suboptimal so I’m still wondering if we could improve phalloidin staining for difficult samples with iteration. I know you don’t find similar improvements in phalloidin staining with iteration but I’m wondering if your phalloidin staining …
It looks like each iteration involves permeabilization. How necessary is this step in each iteration rather than simply rounds of primary and secondary antibodies with washes in between?
Also we’ve found detection of actin with fluorescent phalloidin to require improved signal and reduced background, particularly in photosynthetic cells with a great deal of chlorophyll autofluorescence. This requires 1) low concentrations, 2) reduced incubation time, and 3) brighter fluorophore such as Atto compared to Alexa dyes. For your antibodies, you mention low concentrations also result in low signal, so this is suboptimal so I’m still wondering if we could improve phalloidin staining for difficult samples with iteration. I know you don’t find similar improvements in phalloidin staining with iteration but I’m wondering if your phalloidin staining protocol had been optimized as much as you’ve optimized the antibody concentrations for your 1X designations to minimize signal to noise before performing phalloidin iterations to increase signal. Further, it could be that the absolute target abundance matters for the changes in signal to noise ratio with iteration. So by comparing iteration for low abundance antibody targets with iteration for high abundance non-antibody labeling, you may not see comparable improvements for a non-antibody label. If you were to use this protocol on cells where the f-actin signal is harder to detect than in these cells, might you see improvements with iterative labeling? Or alternatively if you compared antibody iteration with a non-antibody label against a target of lower abundance in the same cells, perhaps the signal to noise difference would change more with iteration? It would be of general interest if iterative staining could also improve signal to noise for low signal or low abundance non-antibody labels.
Thanks for publishing this interesting study!
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