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Background Sperm metabolic pathways that generate energy for motility are compartmentalized within the flagellum. Dysfunctions in metabolic compartments, namely mitochondrial respiration and glycolysis, can compromise motility and male fertility. Studying these compartments is thus required for fertility treatment. However, it is very challenging to capture images of metabolic compartments in motile spermatozoa because the fast beating of the flagellum introduces motion blur. Therefore, most approaches immobilize spermatozoa prior to imaging. Results Our findings indicate that immobilizing sperm alters their metabolic profile, highlighting the necessity for measuring metabolism in spermatozoa during movement. We achieved this by encapsulating mouse epididymis in a hydrogel followed by two-photon fluorescence lifetime imaging microscopy for imaging motile sperm in situ. The autofluorescence of endogenous metabolites—FAD, NADH, and NADPH—enabled us to visualize sperm metabolic compartments without staining. We trained machine learning for automated image segmentation and generated metabolic fingerprints using object-based phasor analysis. We show that metabolic fingerprints of spermatozoa and the mitochondrial compartment (1) can distinguish individual males by genetic background, age, or fecundity status, (2) correlate with fertility, and (3) change with age likely due to increased oxidative metabolism. Conclusions Our approach eliminates the need for sperm immobilization and labeling and captures the native state of sperm metabolism. This technique could be adapted for metabolism-based sperm selection for assisted reproduction.

Clustering of the T-cell receptor (TCR) is thought to initiate downstream signalling. However, the detection of protein clustering with high spatial and temporal resolution remains challenging. Here we establish a Förster resonance energy transfer (FRET) sensor, named CliF, which reports intermolecular associations of neighbouring proteins in live cells. A key advantage of the single-chain FRET sensor is that it can be combined with image correlation spectroscopy (ICS), single-particle tracking (SPT) and fluorescence lifetime imaging microscopy (FLIM). We test the sensor with a light-sensitive actuator that induces protein aggregation upon radiation with blue light. When applied to T cells, the sensor reveals that TCR triggering increases the number of dense TCR–CD3 clusters. Further, we find a correlation between cluster movement within the immunological synapse and cluster density. In conclusion, we develop a sensor that allows us to map the dynamics of protein clustering in live T cells. Cellular signalling is often facilitated by membrane protein clustering, but detection of protein clustering at high spatiotemporal resolution is challenging. Here the authors develop a single-chain FRET sensor they name CliF to look at intermolecular associations and dynamics of TCR-CD3 clusters on the T cell surface.

Juno and CD9 protein, expressed in oolemma, are known to be essential for sperm-oocyte binding and fusion. Although evidence exists that these two proteins cooperate, their interaction has not yet been demonstrated. Here in, we present Juno and CD9 mutual localization over the surface of mouse metaphase II oocytes captured using the 3D STED super-resolution technique. The precise localization of examined proteins was identified in different compartments of oolemma such as the microvillar membrane, planar membrane between individual microvilli , and the membrane of microvilli -free region. Observed variance in localization of Juno and CD9 was confirmed by analysis of transmission and scanning electron microscopy images, which showed a significant difference in the presence of proteins between selected membrane compartments. Colocalization analysis of super-resolution images based on Pearson’s correlation coefficient supported evidence of Juno and CD9 mutual position in the oolemma, which was identified by proximity ligation assay. Importantly, the interaction between Juno and CD9 was detected by co-immunoprecipitation and mass spectrometry in HEK293T/17 transfected cell line. For better understanding of experimental data, mouse Juno and CD9 3D structure were prepared by comparative homology modelling and several protein-protein flexible sidechain dockings were performed using the ClusPro server. The dynamic state of the proteins was studied in real-time at atomic level by molecular dynamics (MD) simulation. Docking and MD simulation predicted Juno-CD9 interactions and stability also suggesting an interactive mechanism. Using the multiscale approach, we detected close proximity of Juno and CD9 within microvillar oolemma however, not in the planar membrane or microvilli -free region. Our findings show yet unidentified Juno and CD9 interaction within the mouse oolemma protein network prior to sperm attachment. These results suggest that a Juno and CD9 interactive network could assist in primary Juno binding to sperm Izumo1 as a prerequisite to subsequent gamete membrane fusion.

Quantitative approaches for characterizing molecular organization of cell membrane molecules under physiological and pathological conditions profit from recently developed super-resolution imaging techniques. Current tools employ statistical algorithms to determine clusters of molecules based on single-molecule localization microscopy (SMLM) data. These approaches are limited by the ability of SMLM techniques to identify and localize molecules in densely populated areas and experimental conditions of sample preparation and image acquisition. We have developed a robust, model-free, quantitative clustering analysis to determine the distribution of membrane molecules that excels in densely labeled areas and is tolerant to various experimental conditions, i.e. multiple-blinking or high blinking rates. The method is based on a TIRF microscope followed by a super-resolution optical fluctuation imaging (SOFI) analysis. The effectiveness and robustness of the method is validated using simulated and experimental data investigating nanoscale distribution of CD4 glycoprotein mutants in the plasma membrane of T cells. The ability to quantify the organization of cell membrane molecules is limited by the density of labeling and experimental conditions. Here, the authors use super-resolution optical fluctuation (SOFI) for molecular density and clustering analyses, and investigate nanoscale distribution of CD4 glycoprotein.

Tumor suppressor p53 is a key player in the cell response to DNA damage that suffers by frequent inactivating aberrations. Some of them disturb p53 oligomerization and influence cell decision between proliferation, growth arrest and apoptosis. Active p53 resides mostly in the nucleus, degradation occurs in the cytoplasm. Acute myeloid leukemia (AML)-related mutation of NPM (NPMmut) induces massive mislocalization of p53 to the cytoplasm, which might be related to leukemia initiation. Since both proteins interact and execute their function as oligomers, we investigated the role of perturbed p53 oligomerization in the p53 mislocalization process in live cells by FLIM (fluorescence lifetime imaging microscopy), fluorescence anisotropy imaging (FAIM), fluorescence cross-correlation spectroscopy (FCCS) and immunochemical methods. On a set of fluorescently labeled p53 variants, monomeric R337G and L344P, dimeric L344A, and multimeric D352G and A353S, we correlated their cellular localization, oligomerization and interaction with NPMmut. Interplay between nuclear export signal (NES) and nuclear localization signal (NLS) of p53 was investigated as well. While NLS was found critical for the nuclear p53 localization, NES plays less significant role. We observed cytoplasmic translocation only for multimeric A353S variant with sufficient stability and strong interaction with NPMmut. Less stable multimer D352G and L344A dimer were not translocated, monomeric p53 variants always resided in the nucleus independently of the presence of NPMmut and NES intactness. Oligomeric state of NPMmut is not required for p53 translocation, which happens also in the presence of the nonoligomerizing NPMmut variant. The prominent structural and functional role of the R337 residue is shown.

T cell activation is initiated when ligand binding to the T cell receptor (TCR) triggers intracellular phosphorylation of the TCR-CD3 complex. However, it remains unknown how biophysical properties of TCR engagement result in biochemical phosphorylation events. Here, we constructed an optogenetic tool that induces spatial clustering of ζ-chain in a light controlled manner. We showed that spatial clustering of the ζ-chain intracellular tail alone was sufficient to initialize T cell triggering including phosphorylation of ζ-chain, Zap70, PLCγ, ERK and initiated Ca2+ flux. In reconstituted COS-7 cells, only Lck expression was required to initiate ζ-chain phosphorylation upon ζ-chain clustering, which leads to the recruitment of tandem SH2 domain of Zap70 from cell cytosol to the newly formed ζ-chain clusters at the plasma membrane. Taken together, our data demonstrated the biophysical relevance of receptor clustering in TCR signaling.

Sperm metabolic pathways that generate energy for motility are compartmentalized within the flagellum. Dysfunctions in metabolic compartments, namely mitochondrial respiration and glycolysis, can compromise motility and male fertility. Studying these compartments is thus required for fertility treatment. However, it is very challenging to capture images of metabolic compartments in motile spermatozoa because the fast beating of the flagellum introduces motion blur. Therefore, most approaches immobilize spermatozoa prior to imaging. Our findings indicate that immobilizing sperm alters their metabolic profile, highlighting the necessity for measuring metabolism in spermatozoa during movement. We achieved this by encapsulating mouse epididymis in a hydrogel followed by two-photon fluorescence lifetime imaging microscopy for imaging motile sperm in situ. The autofluorescence of endogenous metabolites--FAD, NADH, and NADPH--enabled us to visualize sperm metabolic compartments without staining. We trained machine learning for automated image segmentation and generated metabolic fingerprints using object-based phasor analysis. We show that metabolic fingerprints of spermatozoa and the mitochondrial compartment (1) can distinguish individual males by genetic background, age, or fecundity status, (2) correlate with fertility, and (3) change with age likely due to increased oxidative metabolism. Our approach eliminates the need for sperm immobilization and labeling and captures the native state of sperm metabolism. This technique could be adapted for metabolism-based sperm selection for assisted reproduction.

In this study, spherical or hexagonal NaYF4:Yb,Er nanoparticles (UCNPs) with sizes of 25 nm (S-UCNPs) and 120 nm (L-UCNPs) were synthesized by high-temperature coprecipitation and subsequently modified with three kinds of polymers. These included poly(ethylene glycol) (PEG) and poly(N,N-dimethylacrylamide-co-2-aminoethylacrylamide) [P(DMA-AEA)] terminated with an alendronate anchoring group, and poly(methyl vinyl ether-co-maleic acid) (PMVEMA). The internalization of nanoparticles by rat mesenchymal stem cells (rMSCs) and C6 cancer cells (rat glial tumor cell line) was visualized by electron microscopy and the cytotoxicity of the UCNPs and their leaches was measured by the real-time proliferation assay. The comet assay was used to determine the oxidative damage of the UCNPs. An in vivo study on mice determined the elimination route and potential accumulation of UCNPs in the body. The results showed that the L- and S-UCNPs were internalized into cells in the lumen of endosomes. The proliferation assay revealed that the L-UCNPs were less toxic than S-UCNPs. The viability of rMSCs incubated with particles decreased in the order S-UCNP@Ale-(PDMA-AEA) > S-UCNP@Ale-PEG > S-UCNPs > S-UCNP@PMVEMA. Similar results were obtained in C6 cells. The oxidative damage measured by the comet assay showed that neat L-UCNPs caused more oxidative damage to rMSCs than all coated UCNPs while no difference was observed in C6 cells. An in vivo study indicated that L-UCNPs were eliminated from the body via the hepatobiliary route; L-UCNP@Ale-PEG particles were almost eliminated from the liver 96 h after intravenous application. Pilot fluorescence imaging confirmed the limited in vivo detection capabilities of the nanoparticles.

Cancer cell invasion through tissue barriers is the intrinsic feature of metastasis, the most life-threatening aspect of cancer. Detailed observation and analysis of cancer cell behaviour in a 3D environment is essential for a full understanding of the mechanisms of cancer cell invasion. The inherent limits of optical microscopy resolution do not allow to for in-depth observation of intracellular structures, such as invadopodia of invading cancer cells. The required resolution can be achieved using electron microscopy techniques such as FIB-SEM. However, visualising cells in a 3D matrix using FIB-SEM is challenging due to difficulties with localisation of a specific cell deep within the resin block. We have developed a new protocol based on the near-infrared branding (NIRB) procedure that extends the pattern from the surface grid deep inside the resin. This 3D burned pattern allows for precise trimming followed by targeted 3D FIB-SEM. Here we present detailed 3D CLEM results combining confocal and FIB-SEM imaging of cancer cell invadopodia that extend deep into the collagen meshwork.