Biology subjects

Mahlandt, E. K.

Publications and source records attributed to Mahlandt, E. K..

4 recordsLinked to original sources

bioRxiv2021

A turquoise fluorescence lifetime-based biosensor for quantitative imaging of intracellular calcium

The most successful genetically encoded calcium indicators (GECIs) employ an intensity or intensiometric readout. Despite a large calcium-dependent change in fluorescence intensity, the quantification of calcium concentrations with GECIs is problematic, which is further complicated by the sensitivity of all GECIs to changes in the pH in the biological range. Here, we report on a novel sensing strategy in which a conformational change directly modifies the fluorescence quantum yield and fluorescence lifetime of a circular permutated turquoise fluorescent protein. The fluorescence lifetime is an absolute parameter that enables straightforward quantification, eliminating intensity-related artifacts. A new engineering strategy that optimizes lifetime contrast led to a biosensor that shows a 3-fold change in the calcium-dependent quantum yield and a fluorescence lifetime change of 1.3 ns. Additionally, the response of the calcium sensor is insensitive to pH between 6.2-9. As a result, the turquoise GECI enables robust measurements of intracellular calcium concentrations by fluorescence lifetime imaging. We demonstrate quantitative imaging of calcium concentration with the turquoise GECI in single endothelial cells and human-derived organoids. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=188 SRC="FIGDIR/small/449214v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@12beb07org.highwire.dtl.DTLVardef@5337f1org.highwire.dtl.DTLVardef@17db68forg.highwire.dtl.DTLVardef@5ca499_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

Visualizing and quantifying data from timelapse imaging experiments

One obvious feature of life is that it is highly dynamic. The dynamics can be captured by movies that are made by acquiring images at regular time intervals, a method that is also known as timelapse imaging. Looking at movies is a great way to learn more about the dynamics in cells, tissue and organisms. However, science is different from Netflix, in that it aims for a quantitative understanding of the dynamics. The quantification is important for the comparison of dynamics and to study effects of perturbations. Here, we provide detailed processing and analysis methods that we commonly use to analyze and visualize our timelapse imaging data. All methods use freely available open-source software and use example data that is available from an online data repository. The step-by-step guides together with example data allow for fully reproducible workflows that can be modified and adjusted to visualize and quantify other data from timelapse imaging experiments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/432684v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@d04086org.highwire.dtl.DTLVardef@3c304borg.highwire.dtl.DTLVardef@186bf56org.highwire.dtl.DTLVardef@17bbd6d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

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

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, cell migration and wound healing. 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 RhoA 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 RhoA 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 RhoA activity. This enables a broader application of RhoA relocation biosensors, which was demonstrated by using the improved biosensor to visualize RhoA activity, during cell division, during random migration, at the Golgi membrane and induced by G protein-coupled receptor signaling. Due to the improved avidity of the new biosensors for RhoA activity, cellular processes regulated by RhoA can be better understood. O_FIG O_LINKSMALLFIG WIDTH=134 HEIGHT=200 SRC="FIGDIR/small/430250v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1847c24org.highwire.dtl.DTLVardef@f22c92org.highwire.dtl.DTLVardef@14c4aa8org.highwire.dtl.DTLVardef@1b9657d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

Endothelial junctional membrane protrusions serve as hotspots for neutrophil transmigration

Upon inflammation, leukocytes rapidly transmigrate across the endothelium to enter the inflamed tissue. Evidence accumulates that leukocytes use preferred exit sites, though it is not yet clear how these hotspots in the endothelium are defined and how they are recognized by the leukocyte. Using lattice light sheet microscopy, we discovered that leukocytes prefer endothelial membrane protrusions at cell junctions for transmigration. Phenotypically, these junctional membrane protrusions are present in an asymmetric manner, meaning that one endothelial cell shows the protrusion and the adjacent one does not. Consequently, leukocytes cross the junction by migrating underneath the protruding endothelial cell. These protrusions depend on Rac1 activity and by using a photo-activatable Rac1 probe, we could artificially generate local exit-sites for leukocytes. Overall, we have discovered a new mechanism that uses local induced junctional membrane protrusions to facilitate/steer the leukocyte escape/exit from inflamed vessel walls.

cell biology↗