Arp2/3 and Mena/VASP Require Profilin 1 for Actin Network Assembly at the Leading Edge

TDAExplore: Quantitative analysis of fluorescence microscopy images through topology-based machine learning

“…Arp2/3 inactivation with the small molecule inhibitor CK-666 causes a striking rearrangement of actin architecture at the cell boundary without changing total polymerized actin levels. 25,31 Our feature mapping recapitulated these results and showed that the average topological score for CK-666treated cells deviated most strongly from their controls near the cell boundary (Figures 2C and 2D). PFN1 KO (Figures 2E and 2F) and depletion of cofilin (Figures S8A and S8B) also showed differential effects based on subcellular location.…”

“…Here, we consider several microscopy image datasets depicting the actin cytoskeleton where we desire subcellular level information about morphology changes. Our previous publications [22][23][24][25] detail numerous ways to extract information from microscopy images of the actin cytoskeleton using fluorescence intensity values of localized actin probes. These include measuring whole-cell or local fluorescence intensity, performing line scan analysis, and combining intensity-based thresholding with morphology filters to segment and quantify specific types of actin structures.…”

“…Some similarities between the two datasets were expected, since knocking out PFN1 affected most, but not all, cellular actin structures. 25 It was also anticipated that this particular cytoskeletal topology would be associated with the PFN1 KO group, since an abundance of actin puncta in the cell interior was a hallmark of PFN1 KO cells. 25 Image segmentation with TDAExplore reveals subcellular differences between image groups Next, we used TDAExplore to extract spatial information at the subcellular level for our CK-666 and PFN1 KO datasets.…”

“…25 It was also anticipated that this particular cytoskeletal topology would be associated with the PFN1 KO group, since an abundance of actin puncta in the cell interior was a hallmark of PFN1 KO cells. 25 Image segmentation with TDAExplore reveals subcellular differences between image groups Next, we used TDAExplore to extract spatial information at the subcellular level for our CK-666 and PFN1 KO datasets. In a process similar to the previously discussed t-SNE mask generation, patch scores generated from an SVR classifier trained on persistence landscapes were mapped back to their pixels of origin so that topological scores could be visualized on the input image as a mask.…”

Involvement of Actin and Actin-Binding Proteins in Carcinogenesis

“…Although, so far, there are no reports on the effect of silencing of the protein on VM, due to its close involvement in the creation of invasive structures, it may become an attractive research target [ 14 ]. Additionally, the recent study by Skruber et al points to the essential role of profilin-1 in actin filament assembly, especially on the leading edge [ 150 ]. These reports could provide the basis for further research on the link between ABPs manipulation and VM inhibition.…”