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Background
Localization-based super-resolution microscopy resolves macromolecular structures down to a few nanometers by computationally reconstructing fluorescent emitter coordinates from diffraction-limited spots. The most commonly used algorithms are based on fitting parametric models of the point spread function (PSF) to a measured photon distribution. These algorithms make assumptions about the symmetry of the PSF and thus, do not work well with irregular, non-linear PSFs that occur for example in confocal lifetime imaging, where a laser is scanned across the sample. An alternative method for reconstructing sparse emitter sets from noisy, diffraction-limited images is compressed sensing, but due to its high computational cost it has not yet been widely adopted. Deep neural network fitters have recently emerged as a new competitive method for localization microscopy. They can learn to fit arbitrary PSFs, but require extensive simulated training data and do not generalize well. A method to efficiently fit the irregular PSFs from confocal lifetime localization microscopy combining the advantages of deep learning and compressed sensing would greatly improve the acquisition speed and throughput of this method.
Results
Here we introduce ReCSAI, a compressed sensing neural network to reconstruct localizations for confocal dSTORM, together with a simulation tool to generate training data. We implemented and compared different artificial network architectures, aiming to combine the advantages of compressed sensing and deep learning. We found that a U-Net with a recursive structure inspired by iterative compressed sensing showed the best results on realistic simulated datasets with noise, as well as on real experimentally measured confocal lifetime scanning data. Adding a trainable wavelet denoising layer as prior step further improved the reconstruction quality.
Conclusions
Our deep learning approach can reach a similar reconstruction accuracy for confocal dSTORM as frame binning with traditional fitting without requiring the acquisition of multiple frames. In addition, our work offers generic insights on the reconstruction of sparse measurements from noisy experimental data by combining compressed sensing and deep learning. We provide the trained networks, the code for network training and inference as well as the simulation tool as python code and Jupyter notebooks for easy reproducibility.
Background
Bacterial meningitis is a life-threatening disease that occurs when pathogens such as Neisseria meningitidis cross the meningeal blood cerebrospinal fluid barrier (mBCSFB) and infect the meninges. Due to the human-specific nature of N. meningitidis, previous research investigating this complex host–pathogen interaction has mostly been done in vitro using immortalized brain endothelial cells (BECs) alone, which often do not retain relevant barrier properties in culture. Here, we developed physiologically relevant mBCSFB models using BECs in co-culture with leptomeningeal cells (LMCs) to examine N. meningitidis interaction.
Methods
We used BEC-like cells derived from induced pluripotent stem cells (iBECs) or hCMEC/D3 cells in co-culture with LMCs derived from tumor biopsies. We employed TEM and structured illumination microscopy to characterize the models as well as bacterial interaction. We measured TEER and sodium fluorescein (NaF) permeability to determine barrier tightness and integrity. We then analyzed bacterial adherence and penetration of the cell barrier and examined changes in host gene expression of tight junctions as well as chemokines and cytokines in response to infection.
Results
Both cell types remained distinct in co-culture and iBECs showed characteristic expression of BEC markers including tight junction proteins and endothelial markers. iBEC barrier function as determined by TEER and NaF permeability was improved by LMC co-culture and remained stable for seven days. BEC response to N. meningitidis infection was not affected by LMC co-culture. We detected considerable amounts of BEC-adherent meningococci and a relatively small number of intracellular bacteria. Interestingly, we discovered bacteria traversing the BEC-LMC barrier within the first 24 h post-infection, when barrier integrity was still high, suggesting a transcellular route for N. meningitidis into the CNS. Finally, we observed deterioration of barrier properties including loss of TEER and reduced expression of cell-junction components at late time points of infection.
Conclusions
Here, we report, for the first time, on co-culture of human iPSC derived BECs or hCMEC/D3 with meningioma derived LMCs and find that LMC co-culture improves barrier properties of iBECs. These novel models allow for a better understanding of N. meningitidis interaction at the mBCSFB in a physiologically relevant setting.
G-protein-coupled receptors (GPCRs) are hypothesized to possess molecular mobility over a wide temporal range. Until now the temporal range has not been fully accessible due to the crucially limited temporal range of available methods. This in turn, may lead relevant dynamic constants to remain masked. Here, we expand this dynamic range by combining fluorescent techniques using a spot confocal setup. We decipher mobility constants of β\(_{2}\)-adrenergic receptor over a wide time range (nanosecond to second). Particularly, a translational mobility (10 µm\(^{2}\)/s), one order of magnitude faster than membrane associated lateral mobility that explains membrane protein turnover and suggests a wider picture of the GPCR availability on the plasma membrane. And a so far elusive rotational mobility (1-200 µs) which depicts a previously overlooked dynamic component that, despite all complexity, behaves largely as predicted by the Saffman-Delbrück model.
Human induced pluripotent stem cells (hiPSCs) have revolutionized the generation of experimental disease models, but the development of protocols for the differentiation of functionally active neuronal subtypes with defined specification is still in its infancy. While dysfunction of the brain serotonin (5-HT) system has been implicated in the etiology of various neuropsychiatric disorders, investigation of functional human 5-HT specific neurons in vitro has been restricted by technical limitations. We describe an efficient generation of functionally active neurons from hiPSCs displaying 5-HT specification by modification of a previously reported protocol. Furthermore, 5-HT specific neurons were characterized using high-end fluorescence imaging including super-resolution microscopy in combination with electrophysiological techniques. Differentiated hiPSCs synthesize 5-HT, express specific markers, such as tryptophan hydroxylase 2 and 5-HT transporter, and exhibit an electrophysiological signature characteristic of serotonergic neurons, with spontaneous rhythmic activities, broad action potentials and large afterhyperpolarization potentials. 5-HT specific neurons form synapses reflected by the expression of pre- and postsynaptic proteins, such as Bassoon and Homer. The distribution pattern of Bassoon, a marker of the active zone along the soma and extensions of neurons, indicates functionality via volume transmission. Among the high percentage of 5-HT specific neurons (~ 42%), a subpopulation of CDH13 + cells presumably designates dorsal raphe neurons. hiPSC-derived 5-HT specific neuronal cell cultures reflect the heterogeneous nature of dorsal and median raphe nuclei and may facilitate examining the association of serotonergic neuron subpopulations with neuropsychiatric disorders.
Expansion microscopy (ExM) enables super-resolution fluorescence imaging on standard microscopes by physical expansion of the sample. However, the investigation of interactions between different organisms such as mammalian and fungal cells by ExM remains challenging because different cell types require different expansion protocols to ensure identical, ideally isotropic expansion of both partners. Here, we introduce an ExM method that enables super-resolved visualization of the interaction between NK cells and Aspergillus fumigatus hyphae. 4-fold expansion in combination with confocal fluorescence imaging allows us to resolve details of cytoskeleton rearrangement as well as NK cells' lytic granules triggered by contact with an RFP-expressing A. fumigatus strain. In particular, subdiffraction-resolution images show polarized degranulation upon contact formation and the presence of LAMP1 surrounding perforin at the NK cell-surface post degranulation. Our data demonstrate that optimized ExM protocols enable the investigation of immunological synapse formation between two different species with so far unmatched spatial resolution.
Neurotransmitter release is stabilized by homeostatic plasticity. Presynaptic homeostatic potentiation (PHP) operates on timescales ranging from minute- to life-long adaptations and likely involves reorganization of presynaptic active zones (AZs). At Drosophila melanogaster neuromuscular junctions, earlier work ascribed AZ enlargement by incorporating more Bruchpilot (Brp) scaffold protein a role in PHP. We use localization microscopy (direct stochastic optical reconstruction microscopy [dSTORM]) and hierarchical density-based spatial clustering of applications with noise (HDBSCAN) to study AZ plasticity during PHP at the synaptic mesoscale. We find compaction of individual AZs in acute philanthotoxin-induced and chronic genetically induced PHP but unchanged copy numbers of AZ proteins. Compaction even occurs at the level of Brp subclusters, which move toward AZ centers, and in Rab3 interacting molecule (RIM)-binding protein (RBP) subclusters. Furthermore, correlative confocal and dSTORM imaging reveals how AZ compaction in PHP translates into apparent increases in AZ area and Brp protein content, as implied earlier.
Single-molecule super-resolution microscopy (SMLM) techniques like dSTORM can reveal biological structures down to the nanometer scale. The achievable resolution is not only defined by the localization precision of individual fluorescent molecules, but also by their density, which becomes a limiting factor e.g., in expansion microscopy. Artificial deep neural networks can learn to reconstruct dense super-resolved structures such as microtubules from a sparse, noisy set of data points. This approach requires a robust method to assess the quality of a predicted density image and to quantitatively compare it to a ground truth image. Such a quality measure needs to be differentiable to be applied as loss function in deep learning. We developed a new trainable quality measure based on Fourier Ring Correlation (FRC) and used it to train deep neural networks to map a small number of sampling points to an underlying density. Smooth ground truth images of microtubules were generated from localization coordinates using an anisotropic Gaussian kernel density estimator. We show that the FRC criterion ideally complements the existing state-of-the-art multiscale structural similarity index, since both are interpretable and there is no trade-off between them during optimization. The TensorFlow implementation of our FRC metric can easily be integrated into existing deep learning workflows.
Actin cytoskeleton deregulation confers midostaurin resistance in FLT3-mutant acute myeloid leukemia
(2021)
The presence of FMS-like tyrosine kinase 3-internal tandem duplication (FLT3-ITD) is one of the most frequent mutations in acute myeloid leukemia (AML) and is associated with an unfavorable prognosis. FLT3 inhibitors, such as midostaurin, are used clinically but fail to entirely eradicate FLT3-ITD+AML. This study introduces a new perspective and highlights the impact of RAC1-dependent actin cytoskeleton remodeling on resistance to midostaurin in AML. RAC1 hyperactivation leads resistance via hyperphosphorylation of the positive regulator of actin polymerization N-WASP and antiapoptotic BCL-2. RAC1/N-WASP, through ARP2/3 complex activation, increases the number of actin filaments, cell stiffness and adhesion forces to mesenchymal stromal cells (MSCs) being identified as a biomarker of resistance. Midostaurin resistance can be overcome by a combination of midostaruin, the BCL-2 inhibitor venetoclax and the RAC1 inhibitor Eht1864 in midostaurin-resistant AML cell lines and primary samples, providing the first evidence of a potential new treatment approach to eradicate FLT3-ITD+AML. Garitano-Trojaola et al. used a combination of human acute myeloid leukemia (AML) cell lines and primary samples to show that RAC1-dependent actin cytoskeleton remodeling through BCL2 family plays a key role in resistance to the FLT3 inhibitor, Midostaurin in AML. They showed that by targeting RAC1 and BCL2, Midostaurin resistance was diminished, which potentially paves the way for an innovate treatment approach for FLT3 mutant AML.
Revealing the molecular organization of anatomically precisely defined brain regions is necessary for refined understanding of synaptic plasticity. Although three-dimensional (3D) single-molecule localization microscopy can provide the required resolution, imaging more than a few micrometers deep into tissue remains challenging. To quantify presynaptic active zones (AZ) of entire, large, conditional detonator hippocampal mossy fiber (MF) boutons with diameters as large as 10 mu m, we developed a method for targeted volumetric direct stochastic optical reconstruction microscopy (dSTORM). An optimized protocol for fast repeated axial scanning and efficient sequential labeling of the AZ scaffold Bassoon and membrane bound GFP with Alexa Fluor 647 enabled 3D-dSTORM imaging of 25 mu m thick mouse brain sections and assignment of AZs to specific neuronal substructures. Quantitative data analysis revealed large differences in Bassoon cluster size and density for distinct hippocampal regions with largest clusters in MF boutons. Pauli et al. develop targeted volumetric dSTORM in order to image large hippocampal mossy fiber boutons (MFBs) in brain slices. They can identify synaptic targets of individual MFBs and measured size and density of Bassoon clusters within individual untruncated MFBs at nanoscopic resolution.
Sphingolipids, including ceramides, are a diverse group of structurally related lipids composed of a sphingoid base backbone coupled to a fatty acid side chain and modified terminal hydroxyl group. Recently, it has been shown that sphingolipids show antimicrobial activity against a broad range of pathogenic microorganisms. The antimicrobial mechanism, however, remains so far elusive. Here, we introduce 'click-AT-CLEM', a labeling technique for correlated light and electron microscopy (CLEM) based on the super-resolution array tomography (srAT) approach and bio-orthogonal click chemistry for imaging of azido-tagged sphingolipids to directly visualize their interaction with the model Gram-negative bacterium Neisseria meningitidis at subcellular level. We observed ultrastructural damage of bacteria and disruption of the bacterial outer membrane induced by two azido-modified sphingolipids by scanning electron microscopy and transmission electron microscopy. Click-AT-CLEM imaging and mass spectrometry clearly revealed efficient incorporation of azido-tagged sphingolipids into the outer membrane of Gram-negative bacteria as underlying cause of their antimicrobial activity.