Comparing Lifeact and Phalloidin for super-resolution imaging of actin in fixed cells
Wester, Michael J. et al. (2020), Comparing Lifeact and Phalloidin for super-resolution imaging of actin in fixed cells, Dryad, Dataset, https://doi.org/10.5061/dryad.xsj3tx9cn
Visualizing actin filaments in fixed cells is of great interest for a variety of topics in cell biology such as cell division, cell movement, and cell signaling. We investigated the possibility of replacing phalloidin, the standard reagent for super-resolution imaging of F-actin in fixed cells, with the actin binding peptide `lifeact’. We compared the labels for use in single molecule based super-resolution microscopy, where AlexaFluor 647 labeled phalloidin was used in a (d)STORM modality and Atto 655 labeled lifeact was used in a single molecule imaging, reversible binding modality. We found that imaging with lifeact had a comparable resolution in reconstructed images and provided several advantages over phalloidin including lower costs, the ability to image multiple regions of interest on a coverslip without degradation, simplified sequential super-resolution imaging, and more continuous labeling of thin filaments.
Actin structures of HeLa and RBL cells were labeled in two approaches, lifeact-Atto655 and phalloidin-AF647. Data was collected for each method using single-molecule localization microscopy. The shared data include the raw sequences taken for each condition for various number of samples in both HeLa and RBL cells as named. To evaluate the capability of labeling approaches in sequential super-resolution imaging, actin structures and microtubules were labeled in HeLa cells for each treatment.
To create figure 1 & 3 super-resolution images:
To create figure 2 FRC calculation:
To create figure 4 multiple dataset collection:
To create figure 5 sequential super-resolution imaging:
HDF5 files can be loaded into MATLAB. As an example, to access the
images for sample 1, run the following commands in MATLAB:
1) Find the number of sequences for a sample:
Info = h5info('LifeactApproach-HeLaCell-Sample1.h5')
2) Each level of the h5 file hierarchy is named in the 'Groups' structure.
For the data included here, we have two layers: /Channel01/Zposition001/.
To find the number of the sequence:
Num_Dataset = numel(Info.Groups.Groups.Datasets)
3) To load a data set:
DataSet_1 = h5read('RawData\LifeactApproach-HeLaCell-Sample1.h5', ...
All related notes are included in the methods section above or in README files included with files in the collection.
NIH, Award: 1R21EB019589
NIH, Award: P50GM085273
NIH, Award: R01GM109888
NIH, Award: 1R21EB019589