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20 pages, 8833 KiB  
Article
Calcium Indicators with Fluorescence Lifetime-Based Signal Readout: A Structure–Function Study
by Tatiana R. Simonyan, Larisa A. Varfolomeeva, Anastasia V. Mamontova, Alexey A. Kotlobay, Andrey Y. Gorokhovatsky, Alexey M. Bogdanov and Konstantin M. Boyko
Int. J. Mol. Sci. 2024, 25(23), 12493; https://doi.org/10.3390/ijms252312493 - 21 Nov 2024
Viewed by 161
Abstract
The calcium cation is a crucial signaling molecule involved in numerous cellular pathways. Beyond its role as a messenger or modulator in intracellular cascades, calcium’s function in excitable cells, including nerve impulse transmission, is remarkable. The central role of calcium in nervous activity [...] Read more.
The calcium cation is a crucial signaling molecule involved in numerous cellular pathways. Beyond its role as a messenger or modulator in intracellular cascades, calcium’s function in excitable cells, including nerve impulse transmission, is remarkable. The central role of calcium in nervous activity has driven the rapid development of fluorescent techniques for monitoring this cation in living cells. Specifically, genetically encoded calcium indicators (GECIs) are the most in-demand molecular tools in their class. In this work, we address two issues of calcium imaging by designing indicators based on the successful GCaMP6 backbone and the fluorescent protein BrUSLEE. The first indicator variant (GCaMP6s-BrUS), with a reduced, calcium-insensitive fluorescence lifetime, has potential in monitoring calcium dynamics with a high temporal resolution in combination with advanced microscopy techniques, such as light beads microscopy, where the fluorescence lifetime limits acquisition speed. Conversely, the second variant (GCaMP6s-BrUS-145), with a flexible, calcium-sensitive fluorescence lifetime, is relevant for static measurements, particularly for determining absolute calcium concentration values using fluorescence lifetime imaging microscopy (FLIM). To identify the structural determinants of calcium sensitivity in these indicator variants, we determine their spatial structures. A comparative structural analysis allowed the optimization of the GCaMP6s-BrUS construct, resulting in an indicator variant combining calcium-sensitive behavior in the time domain and enhanced molecular brightness. Our data may serve as a starting point for further engineering efforts towards improved GECI variants with fine-tuned fluorescence lifetimes. Full article
(This article belongs to the Collection Feature Papers in Molecular Biophysics)
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Figure 1

Figure 1
<p>Schematics showing the design of chimeric proteins used in the study. At the top, the spatial structure of GCaMP6 is shown, with the mutations required for the EGFP modification. In the center, there is a linear scheme of the GCaMP-type backbone. The numbering of amino acid positions corresponds to those of the unmodified proteins (EGFP and calmodulin). At the bottom (left and right), the modified variants, GCaMP6s-BrUS and GCaMP6s-BrUS-145, are displayed, with the introduced modifications displayed below them.</p>
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<p>Calcium sensitivity of purified GCaMP6s, GCaMP6s-BrUS, and GCaMP6s-BrUS-145 measured in the intensiometric mode. (<b>A</b>) The dependence of fluorescence intensity at 510 nm (λ<sub>ex</sub> = 475 nm) on calcium concentration, expressed as [Ca<sup>2+</sup>]<sub>free</sub> (see <a href="#app1-ijms-25-12493" class="html-app">Supplementary Table S1</a> for details on the correspondence between [Ca<sup>2+</sup>]<sub>free</sub> and [CaEGTA]). (<b>B</b>) Column histogram displaying the relative fluorescence intensity changes observed within the [Ca<sup>2+</sup>]<sub>free</sub> range of 0–39 μM (corresponds to the [CaEGTA] range of 0–10 mM). Standard errors of the mean (S.E.M.) are shown for each data point (<span class="html-italic">n</span> = 3).</p>
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<p>The graph describing the dependence of the amplitude-weighted mean fluorescence lifetime of indicator variants on calcium concentration ([CaEGTA] and [Ca<sup>2+</sup>]<sub>free</sub>; see <a href="#app1-ijms-25-12493" class="html-app">Supplementary Table S1</a> for details). λ<sub>ex</sub> = 450 nm, repetition rate is 20 MHz. Standard errors of the mean (S.E.M.) are shown for each data point (<span class="html-italic">n</span> = 3).</p>
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<p>Comparison of GCaMP6s-BrUS and GCaMP6s-BrUS-145 structures. (<b>A</b>,<b>B</b>) Superposition of GCaMP6s-BrUS and GCaMP6s-BrUS-145 (magenta) structures from two views. Color scheme for GCaMP6s-BrUS is the following: EFGP domain—green, CaM domain—blue, M13 helix—orange, and the linker 314–319—light gray. Chromophore and calcium ions are shown in light and dark gray color for GCaMP6s-BrUS and GCaMP6s-BrUS-145, respectively. Red arrows point to the shift of the linker 314–319 (<b>A</b>) and the C-lobe of the CaM domain (<b>B</b>). (<b>C</b>–<b>F</b>) Differences in the conformation of residues surrounding the chromophore. Panels (<b>C</b>,<b>E</b>) represent GCaMP6s-BrUS structure and (<b>D</b>,<b>F</b>) GCaMP6s-BrUS-145. Solvent molecules are shown as red spheres. Hydrogen bonds are depicted as dashed blue lines.</p>
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<p>Calcium sensitivity of GCaMP6s-BrUS-389K fluorescence. (<b>A</b>) The dependence of fluorescence intensity at 510 nm (λ<sub>ex</sub> = 475 nm) on calcium concentration, expressed as [Ca<sup>2+</sup>]<sub>free</sub>. (<b>B</b>) The graph describing the dependence of the amplitude-weighted mean fluorescence lifetime on calcium concentration ([CaEGTA] and [Ca<sup>2+</sup>]<sub>free</sub>). λ<sub>ex</sub> = 450 nm, repetition rate is 20 MHz. Standard errors of the mean (S.E.M.) are shown for each data point (<span class="html-italic">n</span> = 3).</p>
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<p>Calcium sensitivity of GCaMP6s-BrUS-389K/398G fluorescence. (<b>A</b>) The dependence of fluorescence intensity at 510 nm (λ<sub>ex</sub> = 475 nm) on calcium concentration, expressed as [Ca<sup>2+</sup>]<sub>free</sub>. (<b>B</b>) The graph describing the dependence of the amplitude-weighted mean fluorescence lifetime on calcium concentration ([CaEGTA] and [Ca<sup>2+</sup>]<sub>free</sub>). λ<sub>ex</sub> = 450 nm, repetition rate is 20 MHz. Standard errors of the mean (S.E.M.) are shown for each data point (<span class="html-italic">n</span> = 3).</p>
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19 pages, 6201 KiB  
Article
In Vitro Cell Model Investigation of Alpha-Synuclein Aggregate Morphology Using Spectroscopic Imaging
by Priyanka Swaminathan, Therése Klingstedt, Vasileios Theologidis, Hjalte Gram, Johan Larsson, Lars Hagen, Nina B. Liabakk, Odrun A. Gederaas, Per Hammarström, K. Peter R. Nilsson, Nathalie Van Den Berge and Mikael Lindgren
Int. J. Mol. Sci. 2024, 25(22), 12458; https://doi.org/10.3390/ijms252212458 - 20 Nov 2024
Viewed by 380
Abstract
Recently, it has been hypothesized that alpha-synuclein protein strain morphology may be associated with clinical subtypes of alpha-synucleinopathies, like Parkinson’s disease and multiple system atrophy. However, direct evidence is lacking due to the caveat of conformation-specific characterization of protein strain morphology. Here we [...] Read more.
Recently, it has been hypothesized that alpha-synuclein protein strain morphology may be associated with clinical subtypes of alpha-synucleinopathies, like Parkinson’s disease and multiple system atrophy. However, direct evidence is lacking due to the caveat of conformation-specific characterization of protein strain morphology. Here we present a new cell model based in vitro method to explore various alpha-synuclein (αsyn) aggregate morphotypes. We performed a spectroscopic investigation of the HEK293 cell model, transfected with human wildtype-αsyn and A53T-αsyn variants, using the amyloid fibril-specific heptameric luminescent oligomeric thiophene h-FTAA. The spectral profile of h-FTAA binding to aggregates displayed a blue-shifted spectrum with a fluorescence decay time longer than in PBS, suggesting a hydrophobic binding site. In vitro spectroscopic binding characterization of h-FTAA with αsyn pre-formed fibrils suggested a binding dissociation constant Kd < 100 nM. The cells expressing the A53T-αsyn and human wildtype-αsyn were exposed to recombinant pre-formed fibrils of human αsyn. The ensuing intracellular aggregates were stained with h-FTAA followed by an evaluation of the spectral features and fluorescence lifetime of intracellular αsyn/h-FTAA, in order to characterize aggregate morphotypes. This study exemplifies the use of cell culture together with conformation-specific ligands to characterize strain morphology by investigating the spectral profiles and fluorescence lifetime of h-FTAA, based upon its binding to a certain αsyn aggregate. This study paves the way for toxicity studies of different αsyn strains in vitro and in vivo. Accurate differentiation of specific alpha-synucleinopathies is still limited to advanced disease stages. However, early subtype-specific diagnosis is of the utmost importance for prognosis and treatment response. The potential association of αsyn aggregates morphotypes detected in biopsies or fluids to disease phenotypes would allow for subtype-specific diagnosis in subclinical disease stage and potentially reveal new subtype-specific treatment targets. Notably, the method may be applied to the entire spectrum of neurodegenerative diseases by using a combination of conformation-specific ligands in a physicochemical environment together with other types of polymorphic amyloid variants and assess the conformation-specific features of various protein pathologies. Full article
(This article belongs to the Section Molecular Biology)
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Figure 1

Figure 1
<p>Emission spectra of h-FTAA binding to PFFs fixed at 1 µM concentration with varying concentrations of h-FTAA from (<b>A</b>) 1125 nM to 4500 nM to (<b>B</b>) 141 nM to 563 nM. The samples were excited at 450 nm and the emission was recorded in the range of 500–700 nm. Each spectrum was baseline corrected using h-FTAA emission in PBS only, respectively. The shaded region in each spectrum represents the standard deviation from triplicates of the varied concentrations of h-FTAA while keeping the concentration of PFFs fixed at 1 µM.</p>
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<p>Binding curve of PFFs (1 μM) vs. h-FTAA concentration (red squares). The blue triangles show the signal obtained from only h-FTAA in PBS. The excitation wavelength was 450 nm, and the spectra were collected as in <a href="#ijms-25-12458-f001" class="html-fig">Figure 1</a>. The dashed curves are simulations where the blue dashed line corresponds to 6% QY of h-FTAA in PBS (<a href="#ijms-25-12458-t001" class="html-table">Table 1</a>). Green dot-dashed: 1-site binding K<sub>d</sub> = 25 nM; QY 30%. Red dashed: two-site model, K<sub>d1</sub> = 100 nM; K<sub>d2</sub> = 300 nM. QY(h-FTAA/PFF-site1) 40%; QY(h-FTAA/PFF-site2) 20%. For details of the two-site model, see [<a href="#B32-ijms-25-12458" class="html-bibr">32</a>].</p>
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<p>Hyperspectral imaging and fluorescence lifetime measurements of PFFs stained with 500 nM h-FTAA. (<b>A</b>) Representative fluorescence image and (<b>B</b>) False-color coded FLIM image of PFFs stained with h-FTAA. The sample was excited at 475 nm and the photons were collected in the 500–700 nm range. The color bar to the right represents the lifetime ranging from 0 ns to 2 ns. (<b>C</b>) Spectral analysis of h-FTAA when it is bound to PFFs, showing emission maxima at approximately 540 nm and 580 nm. The five ROIs (red) used to record the emission spectra are shown in (<b>B</b>). (<b>D</b>) Fluorescence decay time distribution recorded from the FLIM image using the same ROIs (red) that were selected for the spectral analysis in (<b>C</b>). The shaded regions in the plots represent the standard deviation.</p>
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<p>Endogenous αsyn expressed in HEK293 cells after transfection with 4 μg human A53T-αsyn or WT-αsyn. (<b>A</b>) Western blot showing αsyn protein bands at approximately 14 kDa in A53T-αsyn and WT-αsyn HEK293 cells which were probed with mouse anti-αsyn antibody Syn211. Representative immunofluorescence images of (<b>B</b>) A53T-αsyn, (<b>C</b>) WT-αsyn HEK293 cells showing localization of αsyn in cytosol, and (<b>D</b>) Untransfected HEK293 cells showing absence of αsyn, when labeled with mouse anti-αsyn antibody Syn211. Scale bar represents 10 µm.</p>
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<p>Representative fluorescence images of HEK293 cells expressing (<b>A</b>) A53T-αsyn or (<b>B</b>) WT-αsyn, seeded with 500 nM human-αsyn PFFs and stained with 1 μM h-FTAA (green) and 5 µM DRAQ5 (red). (<b>C</b>) Untransfected HEK293 cells were also exposed to PFFs, showing minimal fluorescence from h-FTAA. Scale bar represents 10 μm.</p>
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<p>Representative spectral analysis and lifetime distributions of h-FTAA binding to aggregates in A53T-αsyn-HEK293 and WT-αsyn-HEK293 cells. The samples were excited at 475 nm. (<b>A</b>) Emission spectra and (<b>B</b>) lifetime distributions of h-FTAA binding to aggregates in A53T-αsyn (red) and WT-αsyn-HEK293 (green) cells. Shaded areas correspond to the standard deviation of 5 ROIs.</p>
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<p>Representative differential interference contrast (DIC) and confocal microscopy images showing h-FTAA-stained (green), pS129-probed αsyn aggregates (red) in (<b>A</b>) A53T-αsyn-HEK293 cells and (<b>B</b>) WT-αsyn-HEK293 cells. The samples were excited at 475 nm and 650 nm, respectively. (<b>C</b>) Untransfected HEK293 cells, also seeded with PFFs, show no fluorescence from h-FTAA or the anti-αsyn pS129 antibody, indicating absence of pS129-positive αsyn aggregates. Scale bar represents 25 µm.</p>
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<p>Representative spectral analysis and lifetime distributions of h-FTAA-stained, pS129-labeled aggregates in A53T-αsyn-HEK293 and WT-αsyn-HEK293 cells. The samples were excited at 475 nm and 650 nm for h-FTAA and Alexa Fluor 647, respectively. (<b>A</b>) Emission spectra and (<b>B</b>) life-time distributions for h-FTAA-stained, pS129-labeled aggregates in A53T-αsyn-HEK293 and WT-αsyn-HEK293 cells. Shaded areas correspond to the standard deviation of 5 ROIs.</p>
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12 pages, 5537 KiB  
Article
Accompanying Hemoglobin Polymerization in Red Blood Cells in Patients with Sickle Cell Disease Using Fluorescence Lifetime Imaging
by Fernanda Aparecida Borges da Silva, João Batista Florindo, Amilcar Castro de Mattos, Fernando Ferreira Costa, Irene Lorand-Metze and Konradin Metze
Int. J. Mol. Sci. 2024, 25(22), 12290; https://doi.org/10.3390/ijms252212290 - 15 Nov 2024
Viewed by 485
Abstract
In recent studies, it has been shown that fluorescence lifetime imaging (FLIM) may reveal intracellular structural details in unstained cytological preparations that are not revealed by standard staining procedures. The aim of our investigation was to examine whether FLIM images could reveal areas [...] Read more.
In recent studies, it has been shown that fluorescence lifetime imaging (FLIM) may reveal intracellular structural details in unstained cytological preparations that are not revealed by standard staining procedures. The aim of our investigation was to examine whether FLIM images could reveal areas suggestive of polymerization in red blood cells (RBCs) of sickle cell disease (SCD) patients. We examined label-free blood films using auto-fluorescence FLIM images of 45 SCD patients and compared the results with those of 27 control persons without hematological disease. All control RBCs revealed homogeneous cytoplasm without any foci. Rounded non-sickled RBCs in SCD showed between zero and three small intensively fluorescent dots with higher lifetime values. In sickled RBCs, we found additionally larger irregularly shaped intensively fluorescent areas with increased FLIM values. These areas were interpreted as equivalent to polymerized hemoglobin. The rounded, non-sickled RBCs of SCD patients with homogeneous cytoplasm were not different from those of the erythrocytes of control patients in light microscopy. Yet, variables from the local binary pattern-transformed matrix of the FLIM values per pixel showed significant differences between non-sickled RBCs and those of control cells. In a linear discriminant analysis, using local binary pattern-transformed texture features (mean and entropy) of the erythrocyte cytoplasm of normal appearing cells, the final model could distinguish between SCD patients and control persons with an accuracy of 84.7% of the patients. When the classification was based on the examination of a single rounded erythrocyte, an accuracy of 68.5% was achieved. Employing the Linear Discriminant Analysis classifier method for machine learning, the accuracy was 68.1%. We believe that our study shows that FLIM is able to disclose the topography of the intracellular polymerization process of hemoglobin in sickle cell disease and that the images are compatible with the theory of the two-step nucleation. Furthermore, we think that the presented technique may be an interesting tool for the investigation of therapeutic inhibition of polymerization. Full article
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Figure 1
<p>Image of a peripheral blood film of a control case with several normal RBCs. Upper left: auto-fluorescence picture. Upper middle: fluorescence lifetime image: the blue color corresponds to the lifetime of hemoglobin. Surrounding plasma in green/yellow color corresponding to a higher lifetime. A cursor is placed on a RBC (right inferior corner). Upper right: histogram of the lifetime distribution of the image (pseudo-colors according to the rainbow spectrum). Blue represents the shortest lifetime and red is the longest. The histogram shows that hemoglobin has a short lifetime. Below is the fluorescence lifetime decay curve of the selected spot in the image. Every dot represents a single photon.</p>
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<p>Upper left: autofluorescence and FLIM images of a patient with homozygous SS hemoglobinopathy. Two normal-shaped and one sickled RBC. Each of the normal looking ones shows one highly fluorescent dot. The sickled RBC has areas with a higher fluorescence suggestive of polymerization. The histogram on the right side represents the lifetime of the region where the cursor is placed. Lower right is the decay curve of the selected region of interest.</p>
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<p>RBCs from a blood smear of a patient with SC hemoglobinopathy. Left: auto-fluorescence and right FLIM image. In the center, a sickled cell with an irregular heterogeneous area of enhanced fluorescence revealing a higher lifetime value in the FLIM compared to the surrounding cytoplasm. Some of the non-sickled RBCs show highly fluorescent dots.</p>
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<p>RBCs from a blood smear of S beta-thalassemia hemoglobinopathy. Three entire sickled cells with irregular, sometimes heterogeneous areas with enhanced fluorescence revealing higher lifetime values compared to the surrounding cytoplasm. Some of the non-sickled RBCs show highly fluorescent dots.</p>
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<p>Distribution of non-sickled cells in patients with SCD according to the sub-types: SS in black, SC in green, and S thalassemia in orange. There were no significant differences among the different sub-types of SCD.</p>
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<p>Dot plot showing the distribution of LBP mean (Y axis) and LBP entropy (X axis) to show the distribution of each cell in the control group (blue), and SCD: non-sickled cells are in green and sickled cells are in orange. Both parameters were able to discriminate between normal and SCD in 84.7% of the cases.</p>
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16 pages, 5439 KiB  
Article
Unraveling Microviscosity Changes Induced in Cancer Cells by Photodynamic Therapy with Targeted Genetically Encoded Photosensitizer
by Liubov E. Shimolina, Aleksandra E. Khlynova, Vadim V. Elagin, Pavel A. Bureev, Petr S. Sherin, Marina K. Kuimova and Marina V. Shirmanova
Biomedicines 2024, 12(11), 2550; https://doi.org/10.3390/biomedicines12112550 - 8 Nov 2024
Viewed by 485
Abstract
Background: Despite the fundamental importance of cell membrane microviscosity, changes in this biophysical parameter of membranes during photodynamic therapy (PDT) have not been fully understood. Methods: In this work, changes in the microviscosity of membranes of live HeLa Kyoto tumor cells were studied [...] Read more.
Background: Despite the fundamental importance of cell membrane microviscosity, changes in this biophysical parameter of membranes during photodynamic therapy (PDT) have not been fully understood. Methods: In this work, changes in the microviscosity of membranes of live HeLa Kyoto tumor cells were studied during PDT with KillerRed, a genetically encoded photosensitizer, in different cellular localizations. Membrane microviscosity was visualized using fluorescence lifetime imaging microscopy (FLIM) with a viscosity-sensitive BODIPY2 rotor. Results: Depending on the localization of the phototoxic protein, different effects on membrane microviscosity were observed. With nuclear localization of KillerRed, a gradual decrease in microviscosity was detected throughout the entire observation period, while for membrane localization of KillerRed, a dramatic increase in microviscosity was observed in the first minutes after PDT, and then a significant decrease at later stages of monitoring. The obtained data on cell monolayers are in good agreement with the data obtained for 3D tumor spheroids. Conclusions: These results indicate the involvement of membrane microviscosity in the response of tumor cells to PDT, which strongly depends on the localization of reactive oxygen species attack via targeting of a genetically encoded photosensitizer. Full article
(This article belongs to the Special Issue Photodynamic Therapy (3rd Edition))
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Figure 1
<p>The schematic mechanism of action of KillerRed protein as a genetically encoded photosensitizer for PDT. The gene encoding KillerRed is incorporated in cancer cells (HeLa Kyoto) through lentiviral transduction to ensure the expression of the protein in a targeted compartment—the cell nucleus (KillerRed-H2B) or the plasma membrane (KillerRed-PM). PDT with KillerRed results in the formation of ROS via the type I photoreaction, which leads to oxidative damage in the targeting site and other compartments.</p>
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<p>The molecular structure of molecular rotor BODIPY2.</p>
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<p>(<b>A</b>) Localization of the genetically encoded photosensitizer KillerRed in the nucleus and plasma membrane of HeLa cells and of the fluorescent molecular rotor in the plasma membrane. The scale bar is 40 µm, applicable to all images. (<b>B</b>) Photobleaching of KillerRed after PDT. Quantification of the fluorescence intensity in the cells after PDT. Means ± SD, <span class="html-italic">n</span> = 50 cells. The scale bar is 40 µm, applicable to all images. H2B: cells with nuclear localization of KillerRed, PM: cells with membrane localization of KillerRed.</p>
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<p>Cell viability and ROS analysis in cells after PDT with genetically encoded KillerRed protein. (<b>A</b>) Live (green)/dead (red) cells (LD) and ROS assay fluorescence images 10 min and 1 h after PDT. The bar is 40 µm, applicable to all images. (<b>B</b>) Quantitative analysis of dead cells in control and treated cell populations, %. (<b>C</b>) Viability of control and treated cells in 24 h after PDT, determined using the MTT assay. (<b>D</b>) Quantitative analysis of ROS in control and treated cell populations. Fluorescence intensity of DCFH-DA is shown as means ± SD. CNT: control with different localization of KillerRed. H2B: cells with nuclear localization of KillerRed. PM: cells with membrane localization of KillerRed. * <span class="html-italic">p</span> &lt; 0.05 with control; # <span class="html-italic">p</span> &lt; 0.05 with KillerRed-H2B.</p>
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<p>Analysis of products of lipid peroxidation: diene (DC) and triene (TC) conjugates and the Schiff bases (SB) for nuclear (<b>A</b>,<b>B</b>) and membrane localizations (<b>C</b>,<b>D</b>) of KillerRed. Means ± SD, <span class="html-italic">n</span> = 5 measurements. * Statistically significant differences in untreated control with KillerRed (<span class="html-italic">p</span> &lt; 0.05). CNT H2B: control with nuclear localization of KillerRed, CNT PM: control with membrane localization of KillerRed.</p>
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<p>Plasma membrane viscosity in HeLa Kyoto cells with KillerRed during PDT. (<b>A</b>) Representative FLIM images of cells with both localizations of KillerRed. The bar is 40 µm, applicable to all images. (<b>B</b>) Quantification of viscosity of plasma membranes in HeLa Kyoto cells. Means ± SD, <span class="html-italic">n</span> = 100 cells for each time point. * <span class="html-italic">p</span> &lt; 0.05 with control; # <span class="html-italic">p</span> &lt; 0.05 with KillerRed-H2B. CNT KR: control with different localization of KillerRed. H2B: cells with nuclear localization of KillerRed. PM: cells with membrane localization of KillerRed.</p>
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<p>Plasma membrane microviscosity in HeLa tumor spheroids after PDT with KillerRed localized in the nuclei (H2B) or within the plasma membrane (PM). (<b>A</b>) Schematic representation of the spheroid area (shown by the yellow square) imaged by FLIM. The spheroid had adhered to the glass bottom, and the images were acquired from a depth of ~30 μm. Higher-magnification image of the molecular rotor distribution in spheroid cell membranes indicated by the red squares. The scale bar is 80 μm. (<b>B</b>) FLIM images and live/dead (LD) assay of control and treated cells in spheroids. Bar = 80 μm. (<b>C</b>) Morphology of control and treated spheroids. The scale bar is 80 μm. (<b>D</b>) Quantification of membrane microviscosity of spheroid cells after PDT. Means ± SD, <span class="html-italic">n</span> = 4 spheroids, 60 cells in each. (<b>E</b>) Quantitative analysis of dead cells in control and treated cell populations, %. * <span class="html-italic">p</span> &lt; 0.05 with control; # <span class="html-italic">p</span> &lt; 0.05 with KillerRed-H2B. CNT KR: control with different localization of KillerRed. H2B: cells with nuclear localization of KillerRed. PM: cells with membrane localization of KillerRed.</p>
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15 pages, 4456 KiB  
Article
Interaction Dynamics of Plant-Specific Insert Domains from Cynara cardunculus: A Study of Homo- and Heterodimer Formation
by Miguel Sampaio, Sofia Santos, Ana Marta Jesus, José Pissarra, Gian Pietro Di Sansebastiano, Jonas Alvim and Cláudia Pereira
Molecules 2024, 29(21), 5139; https://doi.org/10.3390/molecules29215139 - 30 Oct 2024
Viewed by 536
Abstract
Plant aspartic proteinases (APs) from Cynara cardunculus feature unique plant-specific insert (PSI) domains, which serve as essential vacuolar sorting determinants, mediating the transport of proteins to the vacuole. Although their role in vacuolar trafficking is well established, the exact molecular mechanisms that regulate [...] Read more.
Plant aspartic proteinases (APs) from Cynara cardunculus feature unique plant-specific insert (PSI) domains, which serve as essential vacuolar sorting determinants, mediating the transport of proteins to the vacuole. Although their role in vacuolar trafficking is well established, the exact molecular mechanisms that regulate PSI interactions and functions remain largely unknown. This study explores the ability of PSI A and PSI B to form homo- and heterodimers using a combination of pull-down assays, the mating-based split-ubiquitin system (mbSUS), and FRET-FLIM analyses. Pull-down assays provided preliminary evidence of potential PSI homo- and heterodimer formation. This was conclusively validated by the more robust in vivo mbSUS and FRET-FLIM assays, which clearly demonstrated the formation of both homo- and heterodimers between PSI A and PSI B within cellular environments. These findings suggest that PSI dimerization is related to their broader functional role, particularly in protein trafficking. Results open new avenues for future research to explore the full extent of PSI dimerization and its implications in plant cellular processes. Full article
(This article belongs to the Section Molecular Structure)
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Graphical abstract

Graphical abstract
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<p>(<b>A</b>) Schematic representation of PSI-tagged versions used in pull-down assays. SDS-PAGE analysis of PSI–PSI interactions by pull-down assay at pH 6.8 (<b>B</b>,<b>C</b>) and 7.4 (<b>D</b>,<b>E</b>). (<b>B</b>(<b>a</b>),<b>C,D</b>(<b>a</b>) and <b>E</b>) Inputs and pull-down reactions were analyzed on a silver-stained gel. Each pull-down lane was loaded with 15 μL of pull-down reaction and input lanes were loaded with 1/3 of the amount of purified protein added to each reaction. (<b>B</b>)(<b>b</b>)–(<b>D</b>)(<b>b</b>) Western blot analysis to evaluate the presence of FLAG-tagged PSIs in the pull-down reactions. MW: Molecular Weight (PageRuler<sup>TM</sup> Prestained Protein Ladder, Thermo Scientific, Waltham, MA, USA). Red, green, and blue arrows represent GST-PSIA/PSIB-6xHis, FLAG-PSI A-6xHis, and FLAG-PSIB-6xhis, respectively.</p>
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<p>Split ubiquitin yeast two-hybrid assay. (<b>A</b>) Illustrations represent the bait and prey structures. The bait protein is fused to a typical GPI anchor [<a href="#B22-molecules-29-05139" class="html-bibr">22</a>]. (<b>B</b>) Yeast mating-based split-ubiquitin assay for interaction, including negative control (NubG) and positive control (NubI). Yeast diploids dropped at 1:10 and 1:100 dilutions spotted (<b>left</b> to <b>right</b>) on complete synthetic medium without Trp, Leu, Ura, and Met (CSM-LTUM) to verify mating; on CSM without Trp, Leu, Ura, Ade, His, and Met (CSM-LTUMAH) to verify adenine- and histidine-independent growth; and with Met additions to suppress bait expression.</p>
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<p>FRET-FLIM interaction assay. (<b>A</b>) Schematic representation of the fluorescent protein fusions performed in this study. Blue, yellow, green, and red rectangles represent SP-PSIA, SP-PSIB, green fluorescent protein (GFP), and red fluorescent protein (mCherry), respectively. (<b>B</b>) Mean lifetime graphic representation of PSI A—PSIA/B fluorescent protein pairs. Asterisks represent statistically significant differences in mean fluorescence lifetime with an α threshold of 0.05 and a 95% confidence interval (***, <span class="html-italic">p</span> &lt; 0.0002; ****, <span class="html-italic">p</span> &lt; 0.0001). (<b>C</b>) Subcellular localization of PSI A—PSIA/B fluorescent protein pairs. (<b>D</b>) Mean lifetime graphic representation of PSI B—PSI A/B fluorescent protein pairs. Asterisks represent statistically significant differences in mean fluorescence lifetime with an α threshold of 0.05 and a 95% confidence interval (****, <span class="html-italic">p</span> &lt; 0.0001). (<b>E</b>) Subcellular localization of PSI B—PSIA/B fluorescent protein pairs. SP—signal peptide.</p>
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<p>Bioinformatic analysis of the cardoon PSI A and PSI B amino acidic sequence. (<b>A</b>) Identification of conserved regions between PSI A and PSI B. Analysis performed with NetPhos 3.1 webtool (<a href="https://services.healthtech.dtu.dk/services/NetPhos-3.1/" target="_blank">https://services.healthtech.dtu.dk/services/NetPhos-3.1/</a>, accessed on 21 January 2024). Yellow zones represent conserved regions between PSI A and B while the red asterisk (*) represents a glycosylation site in PSI B. (<b>B</b>) Prediction of phosphorylation sites in both PSIs. Produced with Jalview webtool (<a href="https://www.jalview.org" target="_blank">https://www.jalview.org</a>, accessed on 21 January 2024). (<b>C</b>) Analysis of the hydrophilic potential of PSI A and PSI B amino acid sequence. Produced with Jalview webtool (<a href="https://www.jalview.org/" target="_blank">https://www.jalview.org/</a>, accessed on 21 January 2024) (<b>D</b>) Lipid binding potential prediction of amino acid regions in cardoon PSI A and PSI B. Analysis done with DisoLipPred webtool (<a href="http://biomine.cs.vcu.edu/servers/DisoLipPred/" target="_blank">http://biomine.cs.vcu.edu/servers/DisoLipPred/</a>, accessed on 21 January 2024). (<b>E</b>) Tertiary structure prediction of PSI A and PSI B. Double-edged red arrow is used to show that PSI A possesses a clustered tertiary structure while PSI B is a bit wider. Produced with AlphaFold webtool (<a href="https://alphafold.ebi.ac.uk/" target="_blank">https://alphafold.ebi.ac.uk/</a>, accessed on 21 January 2024). Dashed lines represent the threshold value for putative lipid interaction detected by the software. In all figures, the yellow square represents an uncharacterized but conserved loop region found in both PSIs that has potential for lipid interaction and therefore may interact with membranes.</p>
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22 pages, 10937 KiB  
Article
Modular Nanotransporters Deliver Anti-Keap1 Monobody into Mouse Hepatocytes, Thereby Inhibiting Production of Reactive Oxygen Species
by Yuri V. Khramtsov, Alexey V. Ulasov, Andrey A. Rosenkranz, Tatiana A. Slastnikova, Tatiana N. Lupanova, Georgii P. Georgiev and Alexander S. Sobolev
Pharmaceutics 2024, 16(10), 1345; https://doi.org/10.3390/pharmaceutics16101345 - 21 Oct 2024
Viewed by 619
Abstract
Background/Objectives: The study of oxidative stress in cells and ways to prevent it attract increasing attention. Antioxidant defense of cells can be activated by releasing the transcription factor Nrf2 from a complex with Keap1, its inhibitor protein. The aim of the work was [...] Read more.
Background/Objectives: The study of oxidative stress in cells and ways to prevent it attract increasing attention. Antioxidant defense of cells can be activated by releasing the transcription factor Nrf2 from a complex with Keap1, its inhibitor protein. The aim of the work was to study the effect of the modular nanotransporter (MNT) carrying an R1 anti-Keap1 monobody (MNTR1) on cell homeostasis. Methods: The murine hepatocyte AML12 cells were used for the study. The interaction of fluorescently labeled MNTR1 with Keap1 fused to hrGFP was studied using the Fluorescence-Lifetime Imaging Microscopy–Förster Resonance Energy Transfer (FLIM-FRET) technique on living AML12 cells transfected with the Keap1-hrGFP gene. The release of Nrf2 from the complex with Keap1 and its levels in the cytoplasm and nuclei of the AML12 cells were examined using a cellular thermal shift assay (CETSA) and confocal laser scanning microscopy, respectively. The effect of MNT on the formation of reactive oxygen species was studied by flow cytometry using 6-carboxy-2′,7′-dichlorodihydrofluorescein diacetate. Results: MNTR1 is able to interact with Keap1 in the cytoplasm, leading to the release of Nrf2 from the complex with Keap1 and a rapid rise in Nrf2 levels both in the cytoplasm and nuclei, ultimately causing protection of cells from the action of hydrogen peroxide. The possibility of cleavage of the monobody in endosomes leads to an increase in the observed effects. Conclusions: These findings open up a new approach to specifically modulating the interaction of intracellular proteins, as demonstrated by the example of the Keap1-Nrf2 system. Full article
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<p>The changes in the Nrf2 level in AML12 cells following MNT or sulforaphane addition. MNT<sub>R1</sub> or MNT<sub>0</sub> were added to AML12 cells for the indicated time. The fixed cells were stained by indirect immunofluorescence. Nrf2 was revealed by immunofluorescence (red); cell nuclei were stained with DAPI (blue). (<b>a</b>) Representative images of cells without any MNT addition (no additives); (<b>b</b>) cells after 2 h incubation with 10 µM of sulforaphane; (<b>c</b>,<b>d</b>) cells after incubation for indicated time with 500 nM of MNT<sub>R1</sub> and MNT<sub>0</sub>, respectively. Bar—10 µm.</p>
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<p>Kinetics of changing Nrf2 levels after the addition of MNT<sub>R1</sub> and MNT<sub>0</sub> for the cytoplasm (<b>a</b>) and nuclei (<b>b</b>), respectively. Data are presented as mean ± SE. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Analysis of the interaction between intracellular Keap1-hrGFP and MNT<sub>R1</sub>-AF568 after its addition to AML12 cells with the temporary expression of Keap1-hrGFP. Imaging mean fluorescence lifetimes of hrGFP, τ<sub>m</sub>, in the cell after one hour of incubation with 500 nM MNT<sub>R1</sub>-AF568 (<b>a</b>). Frequency distributions of mean fluorescence lifetimes of hrGFP, τ<sub>m</sub>, in cells that were not treated with MNT<sub>R1</sub>-AF568 (<b>b</b>), incubated for 15 min with 500 nM MNT<sub>R1</sub>-AF568 (<b>c</b>), and incubated for one hour with 500 nM MNT<sub>R1</sub>-AF568 (<b>d</b>). The curves were averaged over 5 to 15 cells. The black lines represent the average curves; the blue lines are a result of their fitting with Gaussian curves; and the red lines show the summation of the Gaussian curves.</p>
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<p>Studying the effect of MNT on the Nrf2 microenvironment by CETSA. (<b>a</b>) Examples of immunoblots of Nrf2 in complex with Keap1 (cell heating), active Nrf2 (the cell lysate with MNT<sub>R1</sub> heating), after 15 min of incubation of AML12 cells with 500 nM MNT<sub>R1</sub> (cell heating), after 15 min of incubation of AML12 cells with 500 nM MNT<sub>0</sub> (cell heating), and after 15 min of incubation of AML12 cells with 500 nM of MNT<sub>R1</sub> at 4 °C (cell heating). (<b>b</b>) Melting curves of Nrf2 in complex with Keap1 (blue curve), active Nrf2 (red curve), after 15 min of incubation of AML12 cells with 500 nM MNT<sub>R1</sub> (black curve), after 15 min of incubation of AML12 cells with 500 nM MNT<sub>0</sub> (green curve), and after 15 min of incubation of AML12 cells with 500 nM of MNT<sub>R1</sub> at 4 °C (brown curve). The data were obtained by a CETSA using immunoblotting with antibodies against Nrf2. The dependences are normalized to the average intensity of the band corresponding to Nrf2 at 37 °C. (<b>c</b>) Melting curves of Nrf2 in complex with Keap1 (blue curve), active Nrf2 (red curve), and incubation of AML12 cells with 500 nM MNT<sub>R1</sub> for 2 min (dark yellow curve), 5 min (wine curve), 10 min (magenta curve), and 15 min (black curve). The data were obtained by a CETSA assay using immunoblotting with antibodies against Nrf2. The dependences are normalized to the average intensity of the band corresponding to Nrf2 at 37 °C. (<b>d</b>) The dependence of the fraction of active Nrf2 at 37 °C on the incubation time of AML12 cells with 500 nM of MNT<sub>R1</sub> (black curve) or MNT<sub>clR1</sub> (red curve). The average values of ± standard error (n = 4–14) are provided.</p>
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<p>Effect of MNTs on ROS generation. The effect of pre-incubating AML12 cells with 500 nM MNT<sub>0</sub> for 15 min on cDCF fluorescence at different time points (1–6 h after adding MNT<sub>0</sub>) is shown in plot (<b>a</b>). The effect of pre-incubating AML12 cells with 500 nM MNT<sub>R1</sub> for 5, 10, and 15 min on cDCF fluorescence at different time points (1–6 h after adding MNT<sub>R1</sub>) is shown in plots (<b>b</b>), (<b>c</b>), and (<b>d</b>), respectively. The effect of pre-incubating AML12 cells with 500 nM MNT<sub>clR1</sub> for 5 min on cDCF fluorescence at different time points (1–6 h after adding MNT<sub>clR1</sub>) is shown in plot (<b>e</b>). Data are presented as mean ± SE (<span class="html-italic">n</span> = 6–18). The significance of the difference between groups with MNT addition and the control group (no MNT) is shown (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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18 pages, 1067 KiB  
Article
Quantitative Analysis of Acquisition Speed of High-Precision FLIM Technologies via Simulation and Modeling
by Jinzheng Lu, Ling Miao, Jiaxing Wen, Qiang Li, Jingwei Chen, Qiang Yang, Xing Zhang, Jin Li, Yuchi Wu, Yue Yang, Sixin Wu, Wenbo Mo and Qiang Xiang
Photonics 2024, 11(10), 973; https://doi.org/10.3390/photonics11100973 - 17 Oct 2024
Viewed by 692
Abstract
In practical applications such as cancer diagnosis and industrial detection, there is a critical demand for fast fluorescence lifetime imaging (Fast-FLIM). The Fast-FLIM systems suitable for complex environments are typically achieved by enhancing the hardware performance of time-correlated single-photon counting (TCSPC), with an [...] Read more.
In practical applications such as cancer diagnosis and industrial detection, there is a critical demand for fast fluorescence lifetime imaging (Fast-FLIM). The Fast-FLIM systems suitable for complex environments are typically achieved by enhancing the hardware performance of time-correlated single-photon counting (TCSPC), with an acquisition speed of about a few frames per second (fps). However, due to the limitation of single-photon acquisition, the imaging speed is still far from the demand of practical application. The synchroscan streak camera (SC) maps signals from the temporal dimension to the spatial dimension, effectively overcoming the long acquisition time caused by single-photon acquisition. This paper constructs a method to calculate the acquisition time for the TCSPC-FLIM and SC-FLIM systems, and it quantitatively compares the speed. The research demonstrates that the main factors limiting the acquisition speed of the FLIM systems are the photon emission rate, the photon counting rate, the required SNR, the dwell time, and the number of parallel channels. In high-quality and large-scale lifetime imaging, the acquisition speed of the SC-FLIM is at least 104 times faster than that of the TCSPC-FLIM. Therefore, the synchroscan streak camera has more significant potential to promote Fast-FLIM. Full article
(This article belongs to the Section Biophotonics and Biomedical Optics)
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<p>Processes for 2D time-domain fluorescence lifetime imaging technique.</p>
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<p>The basic principle of the TCSPC-FLIM system. (<b>a</b>) The process of the TCSPC system capturing a fluorescence decay signal. (<b>b</b>) Histograms formed by single counts. (<b>c</b>) Histogram formed by large cumulative counts.</p>
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<p>The basic principle of the synchroscan SC-FLIM system. (<b>a</b>) The process of the synchroscan SC-FLIM system capturing a fluorescence decay signal. (<b>b</b>) The relationship between the readout camera-captured image and the histogram data. (<b>c</b>) Histogram at position <math display="inline"><semantics> <mrow> <mi>x</mi> <mo>=</mo> <mi>i</mi> </mrow> </semantics></math>.</p>
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<p>Scanning schematic of the FLIM system, where D denotes the detector, and T denotes the timing system. (<b>a</b>) Single-channel point scanning. (<b>b</b>) Multi-channel point scanning. (<b>c</b>) Wide-field scanning.</p>
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<p>Schematic diagram of synchroscan SC-FLIM system.</p>
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<p>Schematic diagram of spatial distribution of fluorescence signals in synchroscan SC-FLIM system. (<b>a</b>) Fluorescence transfer process in different modules of the SC-FLIM system. (<b>b</b>) Spatial resolution of the sample. (<b>c</b>) Spatial schematic of the slit. (<b>d</b>) Resolution of the readout camera.</p>
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<p>Decay curve of the standard deviation of the measured signal (<math display="inline"><semantics> <msub> <mi>σ</mi> <mi>τ</mi> </msub> </semantics></math>) with respect to the <math display="inline"><semantics> <msub> <mi>P</mi> <mrow> <mi>h</mi> <mi>i</mi> <mi>s</mi> <mi>t</mi> </mrow> </msub> </semantics></math>.</p>
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<p>Measurement accuracy of two FLIM systems at different <math display="inline"><semantics> <msub> <mi>R</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>a</mi> <mi>y</mi> </mrow> </msub> </semantics></math> values. (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>a</mi> <mi>y</mi> </mrow> </msub> <mo>=</mo> <mn>4</mn> <mo>%</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>a</mi> <mi>y</mi> </mrow> </msub> <mo>=</mo> <mn>8</mn> <mo>%</mo> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>a</mi> <mi>y</mi> </mrow> </msub> <mo>=</mo> <mn>30</mn> <mo>%</mo> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mi>R</mi> <mrow> <mi>d</mi> <mi>e</mi> <mi>c</mi> <mi>a</mi> <mi>y</mi> </mrow> </msub> <mo>=</mo> <mn>60</mn> <mo>%</mo> </mrow> </semantics></math>.</p>
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<p>Measurement accuracy of two FLIM systems for short-lifetime signals (<math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mn>50</mn> </mrow> </semantics></math> ps and <math display="inline"><semantics> <mrow> <msub> <mi>τ</mi> <mrow> <mi>r</mi> <mi>e</mi> <mi>a</mi> <mi>l</mi> </mrow> </msub> <mo>=</mo> <mn>100</mn> </mrow> </semantics></math> ps).</p>
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<p>Measurement accuracy of two FLIM systems for Erythrosine B (methanol as a solvent).</p>
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13 pages, 1545 KiB  
Article
Phase-Sensitive Fluorescence Image Correlation Spectroscopy
by Andrew H. A. Clayton
Int. J. Mol. Sci. 2024, 25(20), 11165; https://doi.org/10.3390/ijms252011165 - 17 Oct 2024
Viewed by 466
Abstract
Fluorescence lifetime imaging microscopy is sensitive to molecular interactions and environments. In homo-dyne frequency-domain fluorescence lifetime imaging microscopy, images of fluorescence objects are acquired at different phase settings of the detector. The detected intensity as a function of detector phase is a sinusoidal [...] Read more.
Fluorescence lifetime imaging microscopy is sensitive to molecular interactions and environments. In homo-dyne frequency-domain fluorescence lifetime imaging microscopy, images of fluorescence objects are acquired at different phase settings of the detector. The detected intensity as a function of detector phase is a sinusoidal function that is sensitive to the lifetime of the fluorescent species. In this paper, the theory of phase-sensitive fluorescence image correlation spectroscopy is described. In this version of lifetime imaging, image correlation spectroscopy analysis (i.e., spatial autocorrelation) is applied to successive fluorescence images acquired at different phase settings of the detector. Simulations of different types of lifetime distributions reveal that the phase-dependent density of fluorescent objects is dependent on the heterogeneity of lifetimes present in the objects. We provide an example of this analysis workflow to a cervical cancer cell stained with a fluorescent membrane probe. Full article
(This article belongs to the Collection Feature Papers in Molecular Biophysics)
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<p>Phase-sensitive image correlation simulations for two-component lifetime distributions. (<b>a</b>) Lifetime-cluster density distributions. (<b>b</b>) Cluster density as a function of detector phase.</p>
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<p>Phase-sensitive image correlation simulations for Gaussian lifetime distributions. (<b>a</b>) Lifetime distributions. (<b>b</b>) Cluster density as a function of detector phase.</p>
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<p>Phase-sensitive image correlation spectroscopy is sensitive to the width of the lifetime distribution. The vertical axis is the relative deviation in phase-sensitive cluster density and the horizontal axis is the co-efficient of variation in the Lorentzian lifetime distribution (empty circles (central lifetime = 2.5 ns; filled circles; central lifetime = 4 ns). Simulations were generated using Equations (17) and (15). Solid line is a plot of y = x and to guide the eye only.</p>
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<p>Fluorescence image of a cervical cancer cell stained with NBD-C<sub>6</sub>-ceramide probe. The red-orange region denotes the Golgi membrane region, while the blue regions denote the outer (plasma) membranes regions of the cell.</p>
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<p>Phase-sensitive average intensities from rhodamine 6G solution (orange symbols) and from a region of external membrane of a cervical cancer cell stained with the NBD-C<sub>6</sub>-ceramide probe (blue symbols). Solid lines denote fits to Equation (5), using sum-of-least-squares minimization.</p>
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<p>Phase-sensitive image correlation spectroscopy applied to a membrane probe in a cervical cancer cell. (<b>a</b>) Phase-sensitive cluster densities from outer membrane (<b>upper</b>) and Golgi membrane (<b>lower</b> panel); Solid lines are fits to Equations (15) and (16) using sum-of-least-squares minimization. (<b>b</b>) Calculated lifetime histograms from outer membrane (<b>upper</b>) and Golgi membrane (<b>lower</b>).</p>
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12 pages, 2854 KiB  
Article
Multi-Modal Investigation of Metabolism in Murine Breast Cancer Cell Lines Using Fluorescence Lifetime Microscopy and Hyperpolarized 13C-Pyruvate Magnetic Resonance Spectroscopy
by Sarah Erickson-Bhatt, Benjamin L. Cox, Erin Macdonald, Jenu V. Chacko, Paul Begovatz, Patricia J. Keely, Suzanne M. Ponik, Kevin W. Eliceiri and Sean B. Fain
Metabolites 2024, 14(10), 550; https://doi.org/10.3390/metabo14100550 - 15 Oct 2024
Viewed by 712
Abstract
Background/Objectives: Despite the role of metabolism in breast cancer metastasis, we still cannot predict which breast tumors will progress to distal metastatic lesions or remain dormant. This work uses metabolic imaging to study breast cancer cell lines (4T1, 4T07, and 67NR) with [...] Read more.
Background/Objectives: Despite the role of metabolism in breast cancer metastasis, we still cannot predict which breast tumors will progress to distal metastatic lesions or remain dormant. This work uses metabolic imaging to study breast cancer cell lines (4T1, 4T07, and 67NR) with differing metastatic potential in a 3D collagen gel bioreactor system. Methods: Within the bioreactor, hyperpolarized magnetic resonance spectroscopy (HP-MRS) is used to image lactate/pyruvate ratios, while fluorescence lifetime imaging microscopy (FLIM) of endogenous metabolites measures metabolism at the cellular scale. Results: HP-MRS results showed no lactate peak for 67NR and a comparatively large lactate/pyruvate ratio for both 4T1 and 4T07 cell lines, suggestive of greater pyruvate utilization with greater metastatic potential. Similar patterns were observed using FLIM with significant increases in FAD intensity, redox ratio, and NAD(P)H lifetime. The lactate/pyruvate ratio was strongly correlated to NAD(P)H lifetime, consistent with the role of NADH as an electron donor for the glycolytic pathway, suggestive of an overall upregulation of metabolism (both glycolytic and oxidative), for the 4T07 and 4T1 cell lines compared to the non-metastatic 67NR cell line. Conclusions: These findings support a complementary role for HP-MRS and FLIM enabled by a novel collagen gel bioreactor system to investigate metastatic potential and cancer metabolism. Full article
(This article belongs to the Section Cell Metabolism)
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Graphical abstract
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<p>(<b>A</b>) The multi-modal bioreactor design uses a 3D collagen gel cell culture in the MRI-compatible bioreactor chamber with (<b>B</b>) a transparent portal in the base that can be placed on a fluorescence microscope stage for fluorescence lifetime imaging microscopy (FLIM setup). (<b>C</b>) The bioreactor system in the MRI setup adjacent to the volume coil was used for signal excitation and detection. (<b>D</b>) Culture media flow was constantly maintained (green arrow) with temperature control maintained by water bath flow around the culture volume (blue arrow). Hyperpolarized metabolic substrates (13C1-pyruvate in this case) were injected via bolus infusion into base of the culture chamber (red arrow).</p>
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<p>(<b>Top</b>) Example fluorescence lifetime imaging microscopy (FLIM) images showing mean lifetime (τ<sub>m</sub>) for NAD(P)H from non-metastatic (67NR), metastatically dormant (4T07), and metastatic (4T1) murine breast cancer cells (<b>upper images</b>). Cells were imaged at a 740 nm wavelength with a 450/70 nm filter. The color-coded images in the first row (<b>upper images</b>) show that the 67NR cells have a shorter τ<sub>m</sub> (more yellow in color) compared to the longer τ<sub>m</sub> in 4T07 and 4T1 cells (more blue in color). The cross hairs centered on specific cells in each panel indicate where fluorescence life time measurement is localized. (<b>Bottom</b>) Example photon lifetime distribution from a single pixel location as displayed by the SPCImage software (v8.0). Units are in nanoseconds (ns).</p>
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<p>Representative spectra from the 3 cell lines studied, 4T1 (<b>top</b>), 4T07 (<b>middle</b>), and 67NR (<b>bottom</b>), showing the pyruvate substrate (170 ppm, truncated), pyruvate hydrate (178 ppm) and lactate (182 ppm) components of hyperpolarized [1-13C] pyruvate metabolism. A vial of urea was included adjacent to the bioreactor chamber as a reference (163 ppm) for calibration. Elevated lactate is apparent for the 4T1 (highly metastatic) in contrast to the 4T07 and 67NR (non-metastatic) cell lines. Note that the small peak near the lactate frequency for the 67NR spectra was measured to be below the noise threshold by the jMRUI analysis software (v5.2).</p>
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<p>(<b>a</b>) An elevated lactate/pyruvate (Lac/Pyr) ratio was found for the 4T1 (highly metastatic) vs. 67NR (non-metastatic) cell lines, in contrast to (<b>b</b>) where the elevated redox ratio and (<b>c</b>) FAD intensity was found for 4T07 (metastatic-dormant) vs. both the 4T1 (highly metastatic) and 67NR (non-metastatic) cell lines. (<b>d</b>) NADH lifetimes trended higher for both 4T07 (metastatic-dormant) and 4T1 (highly metastatic) cell lines compared to the 67NR (non-metastatic) cell line. Three replicates were performed in parallel for each cell line, for a total of N = 9 data points per cell-line. * indicates statistical significance at <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and ns stands for “not significant”.</p>
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16 pages, 4165 KiB  
Article
A Fresh Look at Islet Isolation from Rabbit Pancreases
by Ekaterina Vasilchikova, Polina Ermakova, Alexandra Bogomolova, Alena Kashirina, Liya Lugovaya, Julia Tselousova, Nasip Naraliev, Denis Kuchin, Elena Zagaynova, Vladimir Zagainov and Alexandra Kashina
Int. J. Mol. Sci. 2024, 25(19), 10669; https://doi.org/10.3390/ijms251910669 - 3 Oct 2024
Viewed by 671
Abstract
Islet transplantation represents a promising therapeutic approach for diabetes management, yet the isolation and evaluation of pancreatic islets remain challenging. This study focuses on the isolation of islets from rabbit pancreases, followed by a comprehensive assessment of their viability and functionality. We developed [...] Read more.
Islet transplantation represents a promising therapeutic approach for diabetes management, yet the isolation and evaluation of pancreatic islets remain challenging. This study focuses on the isolation of islets from rabbit pancreases, followed by a comprehensive assessment of their viability and functionality. We developed a novel method for isolating islet cells from the pancreas of adult rabbits. We successfully isolated viable islets, which were subsequently evaluated through a combination of viability assays, an insulin enzyme-linked immunosorbent assay (ELISA), and fluorescence lifetime imaging microscopy (FLIM). The viability assays indicated a high percentage of intact islets post-isolation, while the insulin ELISA demonstrated robust insulin secretion in response to glucose stimulation. FLIM provided insights into the metabolic state of the islets, revealing distinct fluorescence lifetime signatures correlating with functional viability. Our findings underscore the potential of rabbit islets as a model for studying islet biology and diabetes therapy, highlighting the efficacy of combining traditional assays with advanced imaging techniques for comprehensive functional assessments. This research contributes to the optimization of islet isolation protocols and enhances our understanding of islet functional activity dynamics in preclinical settings. Full article
(This article belongs to the Special Issue Molecular Research on Diabetes)
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<p>An example of islets in the pancreatic tissue. (<b>a</b>) Hematoxylin and eosin staining; black arrows point to the islets. (<b>b</b>) IHC staining; insulin (green), glucagon (red), DAPI (blue). (<b>c</b>) Dithizone staining.</p>
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<p>An example of islets immediately post-isolation and purification; dithizone staining.</p>
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<p>A violin plot depicts distribution of rabbit islet size after isolation. The dots represent each islet’s diameter measurement. The solid line indicates the diameter, while the dotted lines indicate the quartiles.</p>
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<p>An example of viability as measured by calcein-AM and propidium iodide fluorescence on the first day after isolation (<b>a</b>) and on the third day after isolation (<b>b</b>). Calcein-AM is depicted with green fluorescence and propidium iodide is depicted with red fluorescence. (<b>c</b>) Assessment of the viability of rabbit islets on the 1st and 3rd days after isolation. The increase in viability was caused by a decrease in the number of cells, in particular, dead cells, during incubation in the culture medium.</p>
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<p>Evaluation of the functional activity of rabbit islets. (<b>a</b>) Daily secretion of insulin by rabbit islets on the day after isolation. (<b>b</b>) Functional assessment of islets by glucose-stimulated insulin response for differences between insulin secretion during low versus high glucose challenge.</p>
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<p>FLIM of NAD(P)H in isolated islets of rabbit. (<b>a</b>) Pseudo-color-coded images of α1/α2 of the NAD(P)H in pancreatic islets of rabbit by glucose-stimulated insulin response (scale bars: 1–6 (α1/α2)). The scale length in all pictures is 100 µm. (<b>b</b>) Mean values of τm, τ1, τ2, α1, α2 and α1/α2 of the NAD(P)H in pancreatic islets of rabbit by glucose-stimulated insulin response (mean ± SD). ***—<span class="html-italic">p</span> &lt; 0.001 (α1, α2, α1/α2, τm), **—<span class="html-italic">p</span> &lt; 0.01 (τ1).</p>
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13 pages, 4891 KiB  
Article
Förster Resonance Energy Transfer and Enhanced Emission in Cs4PbBr6 Nanocrystals Encapsulated in Silicon Nano-Sheets for Perovskite Light Emitting Diode Applications
by Araceli Herrera Mondragon, Roberto Gonzalez Rodriguez, Noah Hurley, Sinto Varghese, Yan Jiang, Brian Squires, Maoding Cheng, Brooke Davis, Qinglong Jiang, Mansour Mortazavi, Anupama B. Kaul, Jeffery L. Coffer, Jingbiao Cui and Yuankun Lin
Nanomaterials 2024, 14(19), 1596; https://doi.org/10.3390/nano14191596 - 3 Oct 2024
Viewed by 937
Abstract
Encapsulating Cs4PbBr6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs4PbBr6 [...] Read more.
Encapsulating Cs4PbBr6 quantum dots in silicon nano-sheets not only stabilizes the halide perovskite, but also takes advantage of the nano-sheet for a compatible integration with the traditional silicon semiconductor. Here, we report the preparation of un-passivated Cs4PbBr6 ellipsoidal nanocrystals and pseudo-spherical quantum dots in silicon nano-sheets and their enhanced photoluminescence (PL). For a sample with low concentrations of quantum dots in silicon nano-sheets, the emission from Cs4PbBr6 pseudo-spherical quantum dots is quenched and is dominated with Pb2+ ion/silicene emission, which is very stable during the whole measurement period. For a high concentration of Cs4PbBr6 ellipsoidal nanocrystals in silicon nano-sheets, we have observed Förster resonance energy transfer with up to 87% efficiency through the oscillation of two PL peaks when UV excitation switches between on and off, using recorded video and PL lifetime measurements. In an area of a non-uniform sample containing both ellipsoidal nanocrystals and pseudo-spherical quantum dots, where Pb2+ ion/silicene emissions, broadband emissions from quantum dots, and bandgap edge emissions (515 nm) appear, the 515 nm peak intensity increases five times over 30 min of UV excitation, probably due to a photon recycling effect. This irradiated sample has been stable for one year of ambient storage. Cs4PbBr6 quantum dots encapsulated in silicon nano-sheets can lead to applications of halide perovskite light emitting diodes (PeLEDs) and integration with traditional semiconductor materials. Full article
(This article belongs to the Special Issue Nanostructured Materials for Electric Applications)
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<p>XRD patterns of silicon nano-sheets on Si wafer (<b>a</b>), Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets (<b>b</b>), and bulk Cs<sub>4</sub>PbBr<sub>6</sub> (<b>c</b>). XRD peaks from Si wafer substrate are labeled with dashed arrows. XRD peaks from silicon nano-sheets are labeled with squares in (<b>b</b>).</p>
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<p>(<b>a</b>) Zoomed-in TEM image of Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets; (<b>b</b>) TEM image of one piece of sample of Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets for TEM-EDX. TEM-EDX map of Si (<b>c</b>), Pb (<b>d</b>), Br (<b>e</b>), and Cs (<b>f</b>). Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals are pointed out by dashed arrows in (<b>a</b>,<b>b</b>). Same scale bar is used for (<b>b</b>–<b>f</b>). White arrows in (<b>d</b>–<b>f</b>) are for region with strong intensity. Dashed lines in (<b>a</b>,<b>b</b>) indicate nano-sheet orientation.</p>
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<p>(<b>a</b>) TEM image of Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots encapsulated in silicon nano-sheets; (<b>b</b>) size distribution of Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots encapsulated in silicon nano-sheets. (<b>c</b>) High resolution TEM (HRTEM) image of Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots and corresponding FFT. TEM of one piece of sample (<b>d</b>) and its TEM-EDX map of Si (<b>e</b>) and Br (<b>f</b>). Same scale bar is used for (<b>d</b>–<b>f</b>).</p>
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<p>(<b>a</b>) Absorption of bulk Cs<sub>4</sub>PbBr<sub>6</sub> (pink line), Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals (yellow line), and quantum dots (blue line) in DMSO solution. (<b>b</b>) Normalized PL spectra of bulk Cs<sub>4</sub>PbBr<sub>6</sub> (yellow line), Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals (pink line), and quantum dots (blue line) encapsulated in silicon nano-sheets. (<b>c</b>) PL spectra of Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets at 0, 4, 10, 14, 21, and 28 s after UV excitation laser is turned on. (<b>d</b>) PL intensity at two wavelengths (512 nm in red and 490 nm in blue) as a function of UV exposure time.</p>
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<p>(<b>a</b>) PL spectra measured after Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets were exposed to UV 375 nm laser for several minutes. Six of them were measured starting with “1” and ending with “6”. (<b>b</b>,<b>c</b>) Average PL lifetime histogram measured with bandpass filters of 490 ± 5 nm (i.e., 485–495 nm) (<b>b</b>) and 530 ± 20 nm (<b>c</b>). (<b>d</b>) PL intensity decay curves for 490 and 512 nm. (<b>e</b>) Intensity and efficiency of FRET and (<b>f</b>) FRET efficiency histogram for two red regions in (<b>d</b>) as indicated by dashed arrows. (<b>g</b>) Occurred FRET events at different distances. (<b>h</b>) Schematic of elongated Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets. Circles show different crystal sizes. Different sizes lead to different bandgaps for FRET.</p>
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<p>(<b>a</b>) PL spectra of Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots encapsulated in silicon nano-sheets after different lengths of UV laser exposure of 0, 1, 2, 3, 4, 5, 10, 25, and 90 min; (<b>b</b>) PL intensities as a function of UV laser exposure time for 483 nm (red circles) and Pb<sup>2+</sup> ion emission at 410 nm; (<b>c</b>) PL of Pb<sup>2+</sup> ion emission after UV degradation of Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots for 5 h. (<b>d</b>) PL of degraded Cs<sub>4</sub>PbBr<sub>6</sub> quantum dots and pure silicene, excited using UV 325 nm laser.</p>
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<p>The PL intensity of Pb<sup>2+</sup> ion emission and laser tail intensity after a filter on day 1 (<b>a</b>) and day 22 (<b>b</b>). (<b>c</b>) The laser intensity is stable and is used as a reference for the intensity ratio of Pb<sup>2+</sup> ion emission on different days.</p>
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<p>(<b>a</b>) PL spectra in a region of the sample where Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals have three PL peaks at 515 nm, 475 nm, and the weak 410 nm line (as indicated by an arrow) after 0, 2, 4, 10, 30, 50 80, and 120 min of UV 375 nm laser exposure; (<b>b</b>) PL intensities of 515 nm and 475 nm as a function of length of UV 375 nm laser exposure. (<b>c</b>) PL spectra from 3-month-old sample after 0, 2, 3, 4, 5, 10, 20, and 30 min of UV 375 nm laser exposure; (<b>d</b>) PL intensities of 515 nm, 460 nm, and 417 nm as a function of length of UV 375 nm laser exposure.</p>
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<p>(<b>a</b>) PL spectra of 12-month-old sample of Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets at 0 (blue line) and 120 min (red line) after UV excitation laser is turned on. (<b>b</b>) PL intensity at 515 nm as function of UV exposure time. We did not conduct peak intensity fitting for 487 nm. The dashed red line is for visual indication only.</p>
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<p>XRD patterns of Cs<sub>4</sub>PbBr<sub>6</sub> nanocrystals encapsulated in silicon nano-sheets that are 12 months old.</p>
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<p>(<b>a</b>) Normalized PL spectra of CsPbBr<sub>3</sub> with decreasing concentration in silicon nano-sheets. (<b>b</b>) PL spectra of CsPbBr<sub>3</sub> quantum dots encapsulated in silicon nano-sheets after different lengths of UV laser exposure of 0, 1, 2, 4, and 35 min; (<b>c</b>) PL intensities as function of UV laser exposure time for broad peak centered at 466 nm.</p>
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14 pages, 1695 KiB  
Article
Early Detection of Lymph Node Metastasis Using Primary Head and Neck Cancer Computed Tomography and Fluorescence Lifetime Imaging
by Nimu Yuan, Mohamed A. Hassan, Katjana Ehrlich, Brent W. Weyers, Garrick Biddle, Vladimir Ivanovic, Osama A. A. Raslan, Dorina Gui, Marianne Abouyared, Arnaud F. Bewley, Andrew C. Birkeland, D. Gregory Farwell, Laura Marcu and Jinyi Qi
Diagnostics 2024, 14(18), 2097; https://doi.org/10.3390/diagnostics14182097 - 23 Sep 2024
Viewed by 863
Abstract
Objectives: Early detection and accurate diagnosis of lymph node metastasis (LNM) in head and neck cancer (HNC) are crucial for enhancing patient prognosis and survival rates. Current imaging methods have limitations, necessitating new evaluation of new diagnostic techniques. This study investigates the [...] Read more.
Objectives: Early detection and accurate diagnosis of lymph node metastasis (LNM) in head and neck cancer (HNC) are crucial for enhancing patient prognosis and survival rates. Current imaging methods have limitations, necessitating new evaluation of new diagnostic techniques. This study investigates the potential of combining pre-operative CT and intra-operative fluorescence lifetime imaging (FLIm) to enhance LNM prediction in HNC using primary tumor signatures. Methods: CT and FLIm data were collected from 46 HNC patients. A total of 42 FLIm features and 924 CT radiomic features were extracted from the primary tumor site and fused. A support vector machine (SVM) model with a radial basis function kernel was trained to predict LNM. Hyperparameter tuning was conducted using 10-fold nested cross-validation. Prediction performance was evaluated using balanced accuracy (bACC) and the area under the ROC curve (AUC). Results: The model, leveraging combined CT and FLIm features, demonstrated improved testing accuracy (bACC: 0.71, AUC: 0.79) over the CT-only (bACC: 0.58, AUC: 0.67) and FLIm-only (bACC: 0.61, AUC: 0.72) models. Feature selection identified that a subset of 10 FLIm and 10 CT features provided optimal predictive capability. Feature contribution analysis identified high-pass and low-pass wavelet-filtered CT images as well as Laguerre coefficients from FLIm as key predictors. Conclusions: Combining CT and FLIm of the primary tumor improves the prediction of HNC LNM compared to either modality alone. Significance: This study underscores the potential of combining pre-operative radiomics with intra-operative FLIm for more accurate LNM prediction in HNC, offering promise to enhance patient outcomes. Full article
(This article belongs to the Special Issue Optimization of Clinical Imaging: From Diagnosis to Prognosis)
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<p>The overall workflow of predicting LNM using CT and FLIm. The original data used for predicting LNM are the CT and FLIm data. The primary tumor masks of HNC were manually delineated on CT images by an experienced radiologist. Primary tumors in CT images were used to extract radiomic features; FLIm features were extracted from three spectral channels for each point measurement. Two sets of features were generated separately and then fused together. The fused and selected features were further used for the ML model training, validation, and testing. Abbreviations: ML—machine learning, LNM—lymph node metastasis, ROC—receiver operating characteristic, AUC—area under curve.</p>
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<p>AUC comparisons using CT features only, FLIm features only and a combination of FLIm and CT features. (<b>a</b>) Comparison of ROC curves using fused features (purple curve), CT features alone (blue curve), and FLIm features alone (orange curve); (<b>b</b>) AUC performance versus relative distance from the location of the FLIm measurement to the tumor border based solely on fused features (purple curve) and FLIm features alone (orange curve), with yellow histograms illustrating the distribution in the relative distance of FLIm measurements. The relative distance is the ratio of the distance from the point to the tumor border (in centimeters) over the maximum distance within the tumor.</p>
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<p>Comparative ROC curves for varying numbers of features. (<b>a</b>) FLIm-only classifiers: “FLIm-n” indicates that a total number of n FLIm features were selected. (<b>b</b>) CT + FLIm classifiers: “CT-n + FLIm-m” indicates that n CT features and m FLIm features were selected.</p>
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<p>AUC performance and subject distribution for small (&lt;2.0 cm) and large (≥2.0 cm) tumor dimensions spanning two tumor anatomical sites (oropharynx and oral cavity). (<b>a</b>) AUC for CT-only classification; (<b>b</b>) AUC for FLIm-only classification; (<b>c</b>) AUC for combined CT + FLIm classification; and (<b>d</b>) the distribution of subjects by LNM status across varying tumor dimensions and sites. The X-axis divides tumors based on anatomical location (oropharynx vs. oral cavity) and size (&lt;2.0 cm vs. ≥2.0 cm).</p>
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13 pages, 3558 KiB  
Article
Enhancing Therapeutic Response and Overcoming Resistance to Checkpoint Inhibitors in Ovarian Cancer through Cell Cycle Regulation
by Shiqi Wang, Chenggui Luo, Jiaqing Guo, Rui Hu, Binglin Shen, Fangrui Lin, Chenshuang Zhang, Changrui Liao, Jun He, Yiping Wang, Junle Qu and Liwei Liu
Int. J. Mol. Sci. 2024, 25(18), 10018; https://doi.org/10.3390/ijms251810018 - 17 Sep 2024
Viewed by 981
Abstract
Tumor cells invade normal surrounding tissues through continuous division. In this study, we hypothesized that cell cycle regulation changes the immune efficacy of ovarian cancer. To investigate this hypothesis, a Förster resonance energy transfer (FRET) sensor was constructed to characterize the cell activity [...] Read more.
Tumor cells invade normal surrounding tissues through continuous division. In this study, we hypothesized that cell cycle regulation changes the immune efficacy of ovarian cancer. To investigate this hypothesis, a Förster resonance energy transfer (FRET) sensor was constructed to characterize the cell activity in real time. Cell shrinkage caused by apoptosis induces the aggregation of proteins on the cell membrane, leading to variations in the fluorescence lifetime of FRET sensors. Moreover, we tracked cell activity across various cycles following co-culture with an immune checkpoint inhibitor. Consequently, we assessed how cell cycle regulation influences immunotherapy in a tumor mouse model. This approach, which involves inhibiting typical cell cycle processes, markedly enhances the effectiveness of immunotherapy. Our findings suggest that modulating the cycle progression of cancer cells may represent a promising approach to enhance the immune response of ovarian cancer cells and the efficacy of immunotherapy based on immune checkpoint inhibitors. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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Graphical abstract
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<p>The sensitivity of the FRET sensor to apoptosis induced by immune response. (<b>A</b>) The FRET sensor enables the characterization of changes in protein density associated with apoptosis by detecting donor fluorescence lifetime. (<b>B</b>) Average lifetime images and the corresponding phasor plot of the cells expressing Lck-V or Lck-Vm, alongside the cells exhibiting FRET sensor activation during chemotherapy. The scale bar is 100 μm. The lifetime values were assigned pseudocolors based on the color scale. (<b>C</b>) Cytomembrane segmentation accurately analyzed fluorescence lifetime figures in transfected cells, revealing a distribution of quantities across different donor lifetime intervals at the single-cell level. The fluorescence lifetime of individual cells is shown as color spots in different lifetime intervals.</p>
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<p>Apoptosis of cancer cells induced by immunotherapy or chemotherapy. (<b>A</b>) Anti-PD-L1 enhances the recognition of tumor cells by T cells, leading to tumor cell apoptosis. (<b>B</b>) The flow analysis unveiled the apoptosis ratio of OVCAR-3 cells across the experimental groups. (<b>C</b>) Fluorescence lifetime images were acquired from the OVCAR-3 cells expressing Lck-V and co-cultured with T cells in the presence of a complete culture medium or anti-PD-L1 (left). The fluorescence lifetime images obtained from the Lck-Vm-transfected cancer cells co-cultured with T cells in the presence of a complete culture medium, anti-PD-L1, or PTX (right). The corresponding phasor plot images are depicted. Lifetime values are shown using pseudocolors based on the color scale ranging from 0.3 ns to 3.6 ns. The scale bar is 100 μm. (<b>D</b>) The fluorescence lifetime distribution of (<b>C</b>). (<b>E</b>) The FRET efficiency of (<b>C</b>) and the analysis of (<b>B</b>). ODT: OVCAR-3 cells only transfected with the donor and co-cultured with T cells, OFT: OVCAR-3 cells transfected with FRET pairs and co-cultured with T cells, and OFT-an-PD: OVCAR-3 cells transfected with FRET pairs co-cultured with T cells, followed by anti-PD-L1 treatment. A total of over 250 cells from 30 images were individually analyzed, and their lifespan results were statistically evaluated. Statistical significance is indicated by <span class="html-italic">p</span> &lt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.01 (**) and <span class="html-italic">p</span> &lt; 0.0001 (****).</p>
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<p>Unveiling the susceptibility of dormant ovarian cancer cells to T cell-mediated immune surveillance by anti-PD-L1. (<b>A</b>) Ovarian cancer cells undergo a quiescent phase upon serum deprivation. (<b>B</b>) Flow cytometry reveals a shift in the proportion of quiescent cells. (<b>C</b>) FLIM images were acquired from OVCAR-3 cells expressing Lck-V or Lck-Vm under different culture conditions, including a complete medium, or co-cultured with T cells in the presence of a complete culture medium or anti-PD-L1. The corresponding phasor plot and the pseudocolor range spanning from 0.3 ns to 3.6 ns are also shown. The scale bar is 100 μm. (<b>D</b>) The fluorescence lifetime distribution of (<b>B</b>). (<b>E</b>) The fluorescence lifetime distribution and (<b>F</b>) FRET efficiency of each group after statistics. OGD: regulated OVCAR-3 cells only transfected with donor, OGFT: regulated OVCAR-3 cells transfected with FRET pairs and co-cultured with T cells, and OGFT-an-PD: regulated OVCAR-3 cells transfected with FRET pairs co-cultured with T cells, followed by anti-PD-L1 treatment. Over 250 cells from 30 images were individually analyzed, and the lifespan results were statistically assessed. <span class="html-italic">p</span> &lt; 0.001 (***) and <span class="html-italic">p</span> &lt; 0.0001 (****) represents a highly significant value.</p>
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<p>Tumor inhibition in vivo by colchicine in combination with anti-PD-L1. (<b>A</b>) A flow chart depicting the immunotherapeutic approach in a murine tumor model. (<b>B</b>) The combination treatment group exhibited significantly reduced tumor size. (<b>C</b>) Immunofluorescent staining was performed to detect the presence of CD<sup>8+</sup>, CD<sup>4+</sup>, CD<sup>3+</sup>, and CD<sup>163+</sup> immune cells in the spleen tissue. DAPI was used for nuclear staining. The scale bar is 40 μm. (<b>D</b>–<b>G</b>) The cell proportions were compared among different experimental groups. Fluorescence expression in over 15 ROI areas was quantified. <span class="html-italic">p</span> &lt; 0.01 (**), <span class="html-italic">p</span> &lt; 0.001 (***) and <span class="html-italic">p</span> &lt; 0.0001 (****) denotes a highly significant difference.</p>
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<p>The efficacy of combination therapy was assessed using IF staining. (<b>A</b>) Representative images of HE and IF staining for each group. IF staining was performed to detect the presence of CD<sup>8+</sup>, CD<sup>3+</sup>, CD<sup>163+</sup>, and PD-L1 in the tumor tissue. Nuclei are depicted in blue (DAPI). The scale bar is 40 μm. (<b>B</b>–<b>E</b>) T cell and PD-L1 proportions were compared among different experimental groups. Fluorescence expression across more than 15 ROI regions was measured, and the results were statistically evaluated. <span class="html-italic">p</span> &lt; 0.001 (***) and <span class="html-italic">p</span> &lt; 0.0001 (****) shows a highly significant result.</p>
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17 pages, 4891 KiB  
Article
TMEM9B Regulates Endosomal ClC-3 and ClC-4 Transporters
by Margherita Festa, Maria Antonietta Coppola, Elena Angeli, Abraham Tettey-Matey, Alice Giusto, Irene Mazza, Elena Gatta, Raffaella Barbieri, Alessandra Picollo, Paola Gavazzo, Michael Pusch, Cristiana Picco and Francesca Sbrana
Life 2024, 14(8), 1034; https://doi.org/10.3390/life14081034 - 20 Aug 2024
Viewed by 3773
Abstract
The nine-member CLC gene family of Cl chloride-transporting membrane proteins is divided into plasma membrane-localized Cl channels and endo-/lysosomal Cl/H+ antiporters. Accessory proteins have been identified for ClC-K and ClC-2 channels and for the lysosomal ClC-7, but not [...] Read more.
The nine-member CLC gene family of Cl chloride-transporting membrane proteins is divided into plasma membrane-localized Cl channels and endo-/lysosomal Cl/H+ antiporters. Accessory proteins have been identified for ClC-K and ClC-2 channels and for the lysosomal ClC-7, but not the other CLCs. Here, we identified TMEM9 Domain Family Member B (TMEM9B), a single-span type I transmembrane protein of unknown function, to strongly interact with the neuronal endosomal ClC-3 and ClC-4 transporters. Co-expression of TMEM9B with ClC-3 or ClC-4 dramatically reduced transporter activity in Xenopus oocytes and transfected HEK cells. For ClC-3, TMEM9B also induced a slow component in the kinetics of the activation time course, suggesting direct interaction. Currents mediated by ClC-7 were hardly affected by TMEM9B, and ClC-1 currents were only slightly reduced, demonstrating specific interaction with ClC-3 and ClC-4. We obtained strong evidence for direct interaction by detecting significant Förster Resonance Energy Transfer (FRET), exploiting fluorescence lifetime microscopy-based (FLIM-FRET) techniques between TMEM9B and ClC-3 and ClC-4, but hardly any FRET with ClC-1 or ClC-7. The discovery of TMEM9B as a novel interaction partner of ClC-3 and ClC-4 might have important implications for the physiological role of these transporters in neuronal endosomal homeostasis and for a better understanding of the pathological mechanisms in CLCN3- and CLCN4-related pathological conditions. Full article
(This article belongs to the Special Issue Ion Channels and Neurological Disease: 2nd Edition)
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<p>TMEM9B as a putative interactor of ClC-3 and ClC-4. (<b>A</b>). Network of ClC-3 interactors, among which is TMEM9B, from the BioGrid 4.4 database [<a href="#B28-life-14-01034" class="html-bibr">28</a>]. The green circle highlights the TMEM9B entry. (<b>B</b>). Network of ClC-4 interactors, among which there is TMEM9B. (<b>C</b>). Network of TMEM9B interactors, among which are ClC-3, -4, and -5, highlighted by green circles. (<b>D</b>). TMEM9B hydrophobicity plot showing a hydrophobic signal peptide (sequence positions 1–32) and a glycosylated asparagine at sequence position 60 in the extracellular/luminal domain. (<b>E</b>). TMEM9B AlphaFold predicted structure, highlighting, in cyan, the hydrophobic region from sequence positions 99 to 144, and, in magenta, the glycosylated asparagine at position 60. The signal peptide was removed from the AlphaFold structure and the image was created with PyMol.</p>
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<p>Co-expression of ClC-4 and ClC-3 with TMEM9B in <span class="html-italic">Xenopus</span> oocytes. (<b>A</b>). Representative recordings of non-injected oocytes and oocytes injected with ClC-4 and with ClC-4 + TMEM9B evoked by the voltage-clamp protocol are shown on the right. (<b>B</b>). Averaged normalized I-V relationships of ClC-4 with and without TMEM9B. Currents are normalized as described in Methods. (<b>C</b>). Typical voltage clamp current traces of non-injected oocytes and oocytes injected with ClC-3 and co-injected with ClC-3 + TMEM9B in response to the stimulation protocol shown on the right. (<b>D</b>). Averaged normalized I-V currents collected for ClC-3 compared with ClC-3 co-injected with TMEM9B. Note that average currents from non-injected oocytes from the same batches are subtracted in the I-V plots and that, for some data points, error bars are smaller than symbol size.</p>
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<p>Co-expression of ClC-1 with TMEM9B in <span class="html-italic">Xenopus</span> oocytes. Typical current traces recorded from oocytes injected with ClC-1 alone and with TMEM9B (<b>A</b>). Stimulation protocol is shown as inset. (<b>B</b>) shows the normalized conductance of ClC-1 compared with ClC-1 with TMEM9B. For ClC-1, the slope conductance is the most robust parameter to quantify functional expression [<a href="#B20-life-14-01034" class="html-bibr">20</a>]. The error bar indicates SD (n = 3 injections). The star indicates <span class="html-italic">p</span> &lt; 0.05 (Student’s <span class="html-italic">t</span>-test).</p>
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<p>Co-expression with TMEM9B strongly reduced transport currents of ClC-4 in HEK cells. (<b>A</b>). Representative ionic currents elicited by the voltage-clamp protocol shown in the inset in control conditions (left trace) and in the presence of TMEM9B (right trace). (<b>B</b>). Average I-V plot shows a strong reduction of outward ClC-4 currents by TMEM9B (mean ± SEM). (<b>C</b>). Average current values at 200 mV (mean ± SD) (red bar, n = 11, I(200 mV) = 1.15 ± 0.45 nA; blue bar, n = 10, I(200 mV) = 0.14 ± 0.07 nA, <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>TMEM9B modulates the biophysical properties of ClC-3. (<b>A</b>). Representative ClC-3 currents elicited by the voltage-clamp protocol shown in the inset in control conditions (left trace) and in the presence of TMEM9B (right trace).0 (<b>B</b>). Representative recordings from a ClC-3 transfected cell (left trace) and from a cell co-transfected with TMEM9B using long (500 ms) pulses as indicated in the inset. (<b>C</b>). Average I-V plot in the absence (orange) and presence of TMEM9B (light blue, mean ± SEM). (<b>D</b>). Average current values at 200 mV (mean ± SD, orange bar, n = 13, I(200 mV) = 2.06 ± 0.97 nA; light blue bar, n = 13, I(200 mV) = 0.64 ± 0.37 nA; The four stars indicate <span class="html-italic">p</span> = 0.0002 (Student’s <span class="html-italic">t</span>-test). (<b>E</b>). Slowing of current activation by TMEM9B. Activation kinetics of cells co-transfected with TMEM9B was fitted with a double exponential function and values of the extracted time constants are shown as mean ± SD (purple bar: τ<sub>fast</sub> =21.0 ± 6.4 ms; pink bar: τ<sub>slow</sub> =120 ± 75 ms). No such slow kinetics were seen in cells transfected only with ClC-3.</p>
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<p>Co-expression with TMEM9B does not affect ClC-7 transport currents in HEK cells. (<b>A</b>). Representative ClC-7 currents elicited by the voltage-clamp protocol shown in the inset in control conditions (left trace) and in a cell co-transfected with TMEM9B (right trace). (<b>B</b>). Average I-V plot of ClC-7 transfected cells in the absence (green) and presence of TMEM9B (purple, mean ± SEM). (<b>C</b>). Average current values at 140 mV (mean ± SD, green bar, n = 5, I(200 mV) = 1.38 ± 0.58 nA; purple bar, n = 4, I(200 mV) = 1.19 ± 0.59 nA, <span class="html-italic">p</span> = 0.649).</p>
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<p>Subcellular localization of TMEM9B expressed alone. (<b>A</b>). Confocal images of HEK cells transfected with TMEM9B-GFP (green), stained with CellMask_DeepRed (magenta), merged image, and corresponding bright field image. The squared region is shown zoomed on the right. (<b>B</b>). Confocal images of cells transfected with TMEM9B-GFP (green) and stained with Lysotracker_DeepRed (magenta), merged image, and corresponding bright field image. The squared region is shown zoomed on the right. (<b>C</b>). Similar to B, but using mCherry tagged TMEM9B (red).</p>
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<p>Subcellular localization of TMEM9B expressed with CLC proteins. (<b>A</b>). Confocal images of HEK cells co-transfected with TMEM9B-mCherry (red) and ClC-4-GFP (green), stained with CellMask_DeepRed (cyan), the merged image, and the corresponding bright field image. The squared region is shown zoomed on the right. (<b>B</b>). Similar results with inverted tags, i.e., TMEM9B-GFP (green) and ClC-4-mCherry (red). (<b>C</b>). Similar results for cells co-transfected with TMEM9B-mCherry (red) and ClC-3-GFP (green). (<b>D</b>). Similar results for cells co-transfected with TMEM9B-mCherry (red) and ClC-1-GFP (green). (<b>E</b>). Similar results for cells co-transfected with TMEM9B-mCherry (red) and ClC-7-GFP (green).</p>
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<p>FLIM-FRET analysis of TMEM9B co-expressed with CLC proteins. (<b>A</b>). ClC-4-GFP phasor plot with corresponding lifetime value and representative image of a ClC-4-GFP transfected HEK cell. (<b>B</b>). ClC-4-GFP/TMEM9B-mCherry phasor plot with relative lifetime value and representative fluorescent confocal merged image of a ClC-4-GFP/TMEM9B-mCherry co-transfected HEK cell. Here, and in panels D, F, and H, the purple circle indicates the GS-coordinates of the unquenched donor. (<b>C</b>). ClC-3-GFP phasor plot with relative lifetime value and representative fluorescent confocal merged image of a ClC-3-GFP transfected HEK cell. (<b>D</b>). ClC-3-GFP/TMEM9B-mCherry phasor plot with relative lifetime value and representative fluorescent confocal merged image of a ClC-3-GFP/TMEM9B-mCherry co-transfected HEK cell. (<b>E</b>). ClC-1-GFP phasor plot with relative lifetime value and representative image of a ClC-1-GFP transfected HEK cell. (<b>F</b>). ClC-1-GFP/TMEM9B-mCherry phasor plot with relative lifetime value and representative image of a ClC-1-GFP/TMEM9B-mCherry co-transfected HEK cell. (<b>G</b>). ClC-7-GFP phasor plot with relative lifetime value and representative image of a ClC-7-GFP transfected HEK cell. (<b>H</b>). ClC-7-GFP/TMEM9B-mCherry phasor plot with relative lifetime value and representative image of a ClC-7-GFP/TMEM9B-mCherry co-transfected HEK cell. (<b>I</b>). FRET Efficiency analysis comparison with **** <span class="html-italic">p</span> &lt; 0.0001 compared to the other groups.</p>
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9 pages, 1547 KiB  
Communication
Mutation in the Kinase Domain Alters the VEGFR2 Membrane Dynamics
by Michela Corsini, Cosetta Ravelli, Elisabetta Grillo, Mattia Domenichini and Stefania Mitola
Cells 2024, 13(16), 1346; https://doi.org/10.3390/cells13161346 - 13 Aug 2024
Viewed by 771
Abstract
Background: Recently, the substitution R1051Q in VEGFR2 has been described as a cancer-associated “gain of function” mutation. VEGFR2R1051Q phosphorylation is ligand-independent and enhances the activation of intracellular pathways and cell growth both in vitro and in vivo. In cancer, this mutation is [...] Read more.
Background: Recently, the substitution R1051Q in VEGFR2 has been described as a cancer-associated “gain of function” mutation. VEGFR2R1051Q phosphorylation is ligand-independent and enhances the activation of intracellular pathways and cell growth both in vitro and in vivo. In cancer, this mutation is found in heterozygosity, suggesting that an interaction between VEGFR2R1051Q and VEGFR2WT may occur and could explain, at least in part, how VEGFR2R1051Q acts to promote VEGFR2 signaling. Despite this, the biochemical/biophysical mechanism of the activation of VEGFR2R1051Q remains poorly understood. On these bases, the aim of our study is to address how VEGFR2R1051Q influences the biophysical behavior (dimerization and membrane dynamics) of the co-expressed VEGFR2WT. Methods: We employed quantitative FLIM/FRET and FRAP imaging techniques using CHO cells co-transfected with the two forms of VEGFR2 to mimic heterozygosity. Results: Membrane protein biotinylation reveals that VEGFR2WT is more exposed on the cell membrane with respect to VEGFR2R1051Q. The imaging analyses show the ability of VEGFR2WT to form heterodimers with VEGFR2R1051Q and this interaction alters its membrane dynamics. Indeed, when the co-expression of VEGFR2WT/VEGFR2R1051Q occurs, VEGFR2WT shows reduced lateral motility and a minor pool of mobile fraction. Conclusions: This study demonstrates that active VEGFR2R1051Q can affect the membrane behavior of the VEGFR2WT. Full article
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Figure 1

Figure 1
<p><span class="html-italic"><span class="underline">VEGFR2<sup>R1051Q</sup> is less exposed on the cell membrane</span>.</span> (<b>A</b>) VEGFR2<sup>WT</sup> and VEGFR2<sup>R1051Q</sup> were immunoprecipitated from biotinylated CHO cells and blotted for Streptavidin-HRP. VEGFR2 was used as a normalizer. (<b>B</b>) The Western blot quantification of three independent experiments (**, <span class="html-italic">p</span> &lt; 0.01).</p>
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<p><span class="html-italic"><span class="underline">VEGFR2<sup>WT</sup> dimerizes with VEGFR2<sup>R1051Q</sup></span></span>. The FLIM/FRET analysis of the interaction between VEGFR2<sup>R1051Q</sup>-YFP or VEGFR2<sup>WT</sup>-YFP with VEGFR2<sup>WT</sup>-mCherry in the CHO cells (n = 20–25 cell measurements, **, <span class="html-italic">p</span> &lt; 0.01). (<b>A</b>) The lifetime of VEGFR2<sup>WT</sup>-YFP or VEGFR2<sup>R1051Q</sup>-YFP in the presence of VEGFR2WT-mCherry (**, <span class="html-italic">p</span> &lt; 0.01). (<b>B</b>) The representative decay curves of VEGFR2<sup>R1051Q</sup>-YFP or VEGFR2<sup>WT</sup>-YFP in the presence of VEGFR2<sup>WT</sup>-mCherry. (<b>C</b>) The distance of VEGFR2<sup>WT</sup>-YFP or VEGFR2<sup>R1051Q</sup>-YFP and VEGFR2<sup>WT</sup>-mCherry. (<b>D</b>) Representative color-coded FRET efficiency in VEGFR2<sup>WT</sup>-YFP/mCherry-VEGFR2<sup>WT</sup> and VEGFR2<sup>R1051Q</sup>-YFP/VEGFR2<sup>WT</sup>-mCherry. (<b>E</b>) FRET efficiency (%) distribution. (<b>F</b>) Occurrence distribution in a representative cell membrane. (n = 20–25 cell measurements, **, <span class="html-italic">p</span> &lt; 0.01). (<b>G</b>) WB anti-VEGFR2 of immunocomplexes recovered using anti GFP from lysed VEGFR2<sup>WT</sup>-YFP/VEGFR2<sup>WT</sup>, VEGFR2<sup>WT</sup>-YFP/VEGFR2<sup>R1051Q</sup>, or VEGFR2<sup>R1051Q</sup>-YFP/VEGFR2<sup>WT</sup> CHO cells upon treatment with 2mM of DTSSP crosslinker.</p>
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<p><span class="html-italic"><span class="underline">VEGFR2<sup>R1051Q</sup> alters the membrane dynamics of the wild-type receptor</span>.</span> FRAP analysis was performed on the plasma membrane of CHO transfected with VEGFR2<sup>WT</sup>-YFP, VEGFR2<sup>R1051Q</sup>-YFP in the absence or in the presence of untagged VEGFR2<sup>WT</sup>, or VEGFR2<sup>R1051Q</sup>. (<b>A</b>) Diffusion coefficient (1/s); (<b>B</b>) mobile fraction (%); (<b>C</b>) Representative fluorescence recovery curves; (<b>D</b>) representative images acquired for 7 min every 5 s. The bleached areas are indicated by a red square (white bar: 10 μm). The data are representative of n = 20–25 cell measurements. One-way ANOVA was applied associated with the Bonferroni multiple comparison test (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; and ****, <span class="html-italic">p</span> &lt; 0.0001).</p>
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