Visualizing endogenous Rho activity with an improved localization-based, genetically encoded biosensor

Abstract

Rho GTPases are regulatory proteins, which orchestrate cell features such as morphology, polarity and movement. Therefore, probing Rho GTPase activity is key to understanding processes such as development and cell migration. Localization-based reporters for active Rho GTPases are attractive probes to study Rho GTPase-mediated processes, in real time with subcellular resolution in living cells and tissue. Until now, relocation Rho biosensors seem to only be useful in certain organisms and have not been characterized well. In this paper, we systematically examined the contribution of the fluorescent protein and Rho binding peptides, on the performance of localization-based sensors. To test the performance, we compared relocation efficiency and specificity in cell-based assays. We identified several improved localization-based, genetically encoded, fluorescent biosensors for detecting endogenous Rho activity. This enables a broader application of Rho relocation biosensors, which was demonstrated by using the improved biosensor to visualize Rho activity during several cellular processes, such as cell division, migration and G protein-coupled receptor signaling. Due to the improved avidity of the new biosensors for Rho activity, cellular processes regulated by Rho can be better understood.

ARHGAP17 regulates the spatiotemporal activity of Cdc42 at invadopodia

“…This sensor design has been extensively used in the past, particularly in Xenopus studies, but was typically not sensitive enough for mammalian cell studies (Benink and Bement, 2005; Kim et al, 2000; Vaughan et al, 2011). Our new Cdc42 sensor has been designed using the same iterative approach we recently described for a RhoA sensor (Mahlandt et al, 2021). To verify the specificity of the sensor in SUM159 cells, we used an assay that measures the translocation of the sensor to the nucleus when co-expressed with different nuclear localized constitutively active Rho GTPases as we have previously described (Mahlandt et al, 2021).…”

“…Our new Cdc42 sensor has been designed using the same iterative approach we recently described for a RhoA sensor (Mahlandt et al, 2021). To verify the specificity of the sensor in SUM159 cells, we used an assay that measures the translocation of the sensor to the nucleus when co-expressed with different nuclear localized constitutively active Rho GTPases as we have previously described (Mahlandt et al, 2021). Our results show that the dTomato-wGBD sensor only relocates to the nucleus in the presence of constitutively active Cdc42, suggesting it is highly specific for Cdc42 (Fig.…”

Cell-based optimisation and characterisation of genetically encoded, location-based biosensors for Cdc42 or Rac activity

“…Candidates colocalizing with the mitochondrial tagged Rho GTPase were further tested for their potential as localization-based sensors. Since the established Rho localization-based sensors utilize only the GBD and not the full length protein, we tried to identify the GBDs in the candidate proteins (Benink and Bement, 2005;Mahlandt et al, 2021;Piekny and Glotzer, 2000). For the Cdc42 biosensor candidates, the Cdc42/Rac interactive binding motif (CRIB), identified by the consensus sequence [I-S-x-P] (Burbelo et al, 1995;Manser et al, 1994), was found in a number of candidate proteins (Fig.…”

“…To conclude, the best Rac sensor candidate is CYRA-I and its relocation efficiency could potentially still be optimized but that was not pursued in this study. Applying the optimized Cdc42 sensor in a multiplexing experiment and in a primary cell To apply the optimized Cdc42 relocation sensor dimericTomato-WASp(CRIB), a multiplexing experiment with the rGBD based Rho relocation sensor (Benink and Bement, 2005;Mahlandt et al, 2021) was performed. The Rho relocation sensors with the best relocation efficiency was also tagged with dimericTomato, namely dimericTomato2xrGBD.…”

3D imaging for driving cancer discovery

“…Genetically encoded reporters for live 3D imaging have been used to extend the application of live imaging to visualization of key processes in cancer biology (Hirata et al , 2015; Kondo et al , 2021; Ponsioen et al , 2021). Development of novel reporters (Mahlandt et al , 2021), multiplexing approaches that combine several reporters (Regot et al , 2014; Chavez‐Abiega et al , 2022) and improved genome editing technologies (Bollen et al , 2022) can be expected to further expand fluorescent reporter applications and increase the richness of information that can be extracted from live 3D imaging data.…”