Identification of Short Hydrophobic Cell-Penetrating Peptides for Cytosolic Peptide Delivery by Rational Design

Cell-penetrating peptides (CPPs) enhance the cellular uptake of membrane-impermeable molecules. Most CPPs are highly cationic, potentially increasing the risk of toxic side effects and leading to accumulation in organs such as the liver. As a consequence, there is an unmet need for less cationic CPPs. However, design principles for effective CPPs are still missing. Here, we demonstrate a design principle based on a classification of peptides according to accumulated side-chain polarity and hydrophobicity. We show that in comparison to randomly selected peptides, CPPs cover a distinct parameter space. We designed peptides of only six to nine amino acids with a maximum of three positive charges covering this property space. All peptides were tested for cellular uptake and subcellular distribution. Following an initial round of screening we enriched the collection with short and hydrophobic peptides and introduced d-amino acid substitutions and lactam bridges which increased cell uptake, in particular for long-term incubation. Using a GFP complementation assay, for the most active peptides we demonstrate cytosolic delivery of a biologically active cargo peptide

A FRET-based biosensor for measuring Gα13 activation in single cells

<div><p>Förster Resonance Energy Transfer (FRET) provides a way to directly observe the activation of heterotrimeric G-proteins by G-protein coupled receptors (GPCRs). To this end, FRET based biosensors are made, employing heterotrimeric G-protein subunits tagged with fluorescent proteins. These FRET based biosensors complement existing, indirect, ways to observe GPCR activation. Here we report on the insertion of mTurquoise2 at several sites in the human Gα13 subunit, aiming to develop a FRET-based Gα13 activation biosensor. Three fluorescently tagged Gα13 variants were found to be functional based on i) plasma membrane localization and ii) ability to recruit p115-RhoGEF upon activation of the LPA2 receptor. The tagged Gα13 subunits were used as FRET donor and combined with cp173Venus fused to the Gγ2 subunit, as the acceptor. We constructed Gα13 biosensors by generating a single plasmid that produces Gα13-mTurquoise2, Gβ1 and cp173Venus-Gγ2. The Gα13 activation biosensors showed a rapid and robust response when used in primary human endothelial cells that were exposed to thrombin, triggering endogenous protease activated receptors (PARs). This response was efficiently inhibited by the RGS domain of p115-RhoGEF and from the biosensor data we inferred that this is due to GAP activity. Finally, we demonstrated that the Gα13 sensor can be used to dissect heterotrimeric G-protein coupling efficiency in single living cells. We conclude that the Gα13 biosensor is a valuable tool for live-cell measurements that probe spatiotemporal aspects of Gα13 activation.</p></div

Insertion of a fluorescent protein at different positions in Gα13.

<p>(A) The protein structure of human Gα13 (PDB ID: 1ZCB). The highlighted residues indicate the amino acid preceding the inserted fluorescent protein. Successful sites for inserting mTurquoise2-Δ9 into Gα13 in pink and unsuccessful sites in orange. (B) A partial protein sequence alignment (full alignment see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193705#pone.0193705.s001" target="_blank">S1 Fig</a>) of different Gα classes. The highlighted residues indicate the amino acid preceding the inserted fluorescent protein (or luciferase). In bold, the sites that were previously used to insert Rluc [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0193705#pone.0193705.ref026" target="_blank">26</a>]. Insertion of mTurquoise2-Δ9 in Gα13 after residue Q144 (black) was based on homology with previous insertions in Gαq and Gαi (black). Successful sites for inserting mTurquoise2-Δ9 (R128, A129 and R140) in pink and unsuccessful sites (L106 and L143) in orange. The numbers indicated below the alignment correspond with the Gα13 variant numbers, used throughout the manuscript. The colors under the alignment match with the colors of the αHelices shown in (A). (C) Confocal images of the tagged Gα13 variants transiently expressed in HeLa cells. The numbers in the left bottom corner of each picture indicate the number of cells that showed plasma membrane localization out of the total number of cells analyzed. The tagged Gα13 variants also localize to structures inside the cell, which are presumably endomembranes,. The width of the images is 76μm.</p

Effects of the p115-RhoGEF RGS domain on Gα13.2 activity and cell morphology.

<p>(A) Normalized ratiometric traces (upper graphs) and corresponding YFP and CFP traces (lower graphs) (dotted lines depict 95% CI) of HUVECs that were transfected with either the Gα13.2 FRET sensor and Lck-mCherry (Control, <i>n</i> = 11) or the Gα13.2 FRET sensor and Lck-mCherry-RGS (+ RGS, <i>n</i> = 13). Cells were stimulated at t = 110s. (B) Ratiometric images of representative cells measured in (A). Cool colors represent low YFP/CFP ratios, corresponding to emission ratios (ERs) on the right.(C) Cell area change of the cells measured in (B), visualized according to the LUT panel on the right. Dotplots on the right represent individual measurements (± 95% CI) of corresponding cells measured in (A). Image width = 54μm.</p

Direct observation of Gα13 and Gαq activation by different GPCRs.

<p>Normalized ratio-metric FRET traces of HeLa cells transfected with the Gq sensor (grey line) or the G13.2 sensor (black line) (dotted lines depict 95% CI). (A) As a control, cells expressing only the Gq (<i>n</i> = 37) or G13.2 (<i>n</i> = 20) sensor were measured. Agonists were sequentially added after 50s, 150s and 230s of imaging. (B) Ratio traces of cells transfected with an untagged LPA2 receptor next to the Gαq (<i>n</i> = 13 (out of 60 in total)) or the Gα13.2 (<i>n</i> = 14 (out of 37 in total)), stimulated at t = 50s. (C) Ratio traces of cells transfected with AngiotensinII type 1 receptor-P2A-mCherry next to the Gαq (<i>n</i> = 22) or the Gα13.2 (<i>n</i> = 9) sensor, stimulated at t = 50s. (D) Ratio traces of cells transfected with an untagged kiss-receptor next to the Gαq (<i>n</i> = 13) or the Gα13.2 (<i>n</i> = 30) sensor, stimulated at t = 50s (indicated with the arrowhead).</p

Effect of SHP2 depletion on IL2 expression.

<p>SHP2 KD and wt Jurkat E6.1 T cells were stimulated with PMA + ionomycin (+), αCD3 & αCD28, αCD3 alone, αCD28 alone or were left unstimulated (–) for 22 h. IL2 in the supernatants was quantified by sandwich ELISAs. Given are the absorption values ± SEM. The p-values are from a full factorial two-way ANOVA and represent the significance of the overall corrected model (corr m), the effect of CD28 expression (CD28 expr), the effect of the stimulus and the interaction factor (int fact) between stimuli and CD28 expression. For all conditions <i>n</i> = 3 samples, all from a single experiment representative of four independent experiments.</p

Quantification of the effect of CD28 expression on cell surface spreading and tyrosine phosphorylation.

<p>The original images of the experiment of Fig. 2 were quantified (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079277#pone.0079277.s009" target="_blank">Macro S1</a>) and the values were normalized to the mean value of the measured property within that image. Normalized values of experiments with inverted stamp and overlay configurations were pooled. The graphs show the mean ± SEM. <i>A-C</i>) Cells stimulated with stripes containing αCD3 and stripes containing αCD28. (<i>n</i> = 10 images from two separate samples in which stamp and overlay stimuli were reversed (Fig. 2<i>B & C</i>) in total counting 1010 CD28 low and 127 CD28 high cells). <i>D-F</i>) Cells stimulated with stripes containing αCD3 and stripes containing unspecific IgG2a only. (<i>n</i> = 10 images from two separate samples in which stamp and overlay stimuli were reversed (Fig. 2<i>D & E</i>) in total counting 921 CD28 low and 97 CD28 high cells). <i>G-I</i>) Cells stimulated with stripes containing unspecific IgG2a only and stripes containing αCD28. (<i>n</i> = 10 images from two separate samples in which stamp and overlay stimuli were reversed (Fig. 2<i>F & G</i>) in total counting 1006 CD28 low and 165 CD28 high cells). <i>A, D & G</i>) The background-corrected, αphosphotyrosine intensity per surface area. Corrected model p-values were determined by two-way factorial ANOVAs in which no interaction terms were included. <i>B, E & H</i>) The contact surface area per cell. Two-sample T-tests were used to generate the p-values. C, <i>F & I</i>) The integrated, background-corrected, αphosphotyrosine intensity per cell (Two-sample T-tests).</p

Image processing of phosphoPLCγ1 signals and cluster formation.

<p>Overview of the image processing protocol as described in Materials and Methods and used for the analysis of the experiments described in Fig. 4. In order to resolve clusters in print, an enlarged segment of a microscopy image labeled with αphospho-PLCγ1 (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079277#pone.0079277.s003" target="_blank">Fig. S3</a>) is shown as an example. Image processing and quantification was done on a per image basis. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0079277#pone.0079277.s010" target="_blank">Macro S2</a> describes the full procedure utilized to analyze the images. In short, the pPLCγ1 signal was thresholded to generate a binary mask of all cells. This image was inverted to generate a mask of the background signal. The CFSE image was thresholded and was used in combination with the mask of all cells to generate a mask of CFSE labeled cells and a mask of unlabeled cells. The image of the printed stripes was thresholded to generate a mask of the printed structures and inversed to also generate a mask of the overlaid areas. Combining the masks of the printed structures and overlaid areas with the masks of the cells formed the masks of the CFSE labeled cells on stamped stripes, the CFSE labeled cells on overlaid structures, the unlabeled cells on stamped stripes and the unlabeled cells on overlaid structures. These four masks were used to measure the surface areas the cells covered on both surfaces. Combining the stripe and overlay masks with the background mask enabled the measurement of surface areas not covered by cells. The last six generated masks were, in turn, applied to the original pPLCγ1 image and from the resulting images the total pPLCγ1 signal per condition could be determined. Together with the total surface areas of the specific condition, the signal intensity per µm² was calculated. Surface specific background corrections were applied. In addition, a binary cluster mask was generated from the pPLCγ1 image. This mask was segmented using the four masks of cells on surfaces creating four new masks. From these masks cluster numbers were counted and by applying them to the original pPLCγ1 image cluster intensities could be determined. Finally, the cell numbers per image were determined by eye using the original transmission images and the cell masks. The various colors correspond to the graphs in Fig. 6 and indicate which masks and images are required to produce the particular data.</p

Detection of the stimulus dependence of total tyrosine phosphorylation (<i>B</i>) and phosphoY783 PLCγ1 (<i>C</i>) in Jurkat cells and SHP2 KD cells.

<p><i>A</i>) For the side-by-side analysis of signaling in Wt and SHP2 KD Jurkat E6.1 T cells, one of the lines was labeled with the cell tracer CFSE. After overnight serum starvation the cells are pooled and incubated on micropatterned, stimulating surfaces for 10 min. Subsequently, the cells are fixed with 3% PFA, permeabilized and immunolabeled for the detection of signaling clusters. <i>B & C</i>) In the top panels, SHP2 KD cells are CFSE labeled and in the bottom panels, wt cells are labeled. Panels from left to right: transmission images; CFSE; immunofluorescence; overlay of the stamped pattern (blue) and the immunolabel (grayscale). In the overlay panels the contrast and brightness for both channels were adjusted proportionally for clarity. 12.5 µg/ml αCD3 + 12.5 µg/ml αCD28 coated stamps were used to generate a striped pattern which was overlaid with 5 µg/ml αCD3. CFSE channels were recorded with saturated signals to facilitate image processing. Scale bars 20 µm.</p

Quantification of the effects of CD28 costimulation and SHP2 deficiency.

<p>The values acquired through image segmentation as described in Fig. 5 were normalized to the mean value of the specific property for that image. The information of multiple images from multiple experiments was used for further analyses. The graphs depict the stimulus and SHP2 dependence of spreading and tyrosine phosphorylation showing the mean ± SEM (based on number of images) of the respective property. KD  =  SHP2 knock-down E6.1 Jurkat cells; wt  =  wild type E6.1 Jurkat cells; 3  =  stripes of αCD3 alone; 3+28  =  αCD3+αCD28-containing stripes (Fig. 4). The colored squares correspond to the colors bordering images and masks in Fig. 5 used to retrieve the data required for the graph in question. Corrected model p-values were determined by two-way factorial ANOVAs in which no interaction terms were included (<i>A-C & E-G</i>) or two-sample T-tests (D <i>& H-J</i>). <i>A-D</i>) Cells labeled with the αphosphotyrosine antibody (<i>n</i> = 15 images resulting from three separate experiments with varying CFSE/unlabeled and stamp/overlay conditions in total containing 861 KD and 615 wt cells). <i>E-H</i>) Cells labeled with the αphosphoY783-PLCγ1 antibody (<i>n</i> = 26 images resulting from five separate experiments with varying CFSE/unlabeled and stamp/overlay conditions in total containing 1804 KD and 1502 wt cells). <i>A & E</i>) Average, background-corrected, overall intensity per surface area. <i>B & F</i>) Average, background-corrected intensity of cluster pixels. <i>C & G</i>) Average number of clusters per surface area. <i>D & H</i>) Average number of clusters per cell. <i>I & J</i>) The average contact surface area per cell (<i>I</i>) and surface-preference-score (<i>J</i>, see text) were determined from pooled data from the phosphoTyr and phosphoY783 PLCγ1 experiments (<i>n</i> = 41 images from 8 experiments with varying CFSE/unlabeled and stamp/overlay conditions in total containing 2665 KD and 2117 wt cells).</p