Coupling Image Restoration and Segmentation: A Generalized Linear Model/Bregman Perspective

An accurate unsupervised extraction of retinal vasculature using curvelet transform and classical morphological operators

BACKGROUND

Many ophthalmic disorders such as diabetic retinopathy and hypertension can be early diagnosed by analyzing changes related to the vascular structure of the retina. Accuracy and efficiency of the segmentation of retinal blood vessels are important parameters that can help the ophthalmologist to better characterize the targeted anomalies.

METHOD

In this work, we propose a new method for accurate unsupervised automatic segmentation of retinal blood vessels based on a simple and adequate combination of classical filters. Initially, contrast of vessels in retinal image is significantly improved by adding the Curvelet Transform to commonly used Contrast-Limited Adaptive Histogram Equalization technique. Afterwards, a morphological operator using Top Hat is applied to highlight vascular network. Then, a global threshold-based Otsu technique using minimum of intra-class variance is applied for vessel detection. Finally, a cleanup operation based on Match Filter and First Derivative Order Gaussian with fixed parameters is used to remove unwanted or isolated segments. We test the proposed method on images from two publicly available STARE and DRIVE databases.

RESULTS

We achieve in terms of sensitivity, specificity and accuracy the respective average performances of 0.7407, 0.9878 and 0.9667 on the DRIVE database, then 0.7028, 0.9755 and 0.9507 on the STARE database.

CONCLUSIONS

Compared to some recent similar work, the obtained results are quite promising and can thus contribute to the optimization of automatic tools to aid in the diagnosis of eye disorders.

BDNF and TRiC-inspired reagent rescue cortical synaptic deficits in a mouse model of Huntington's disease

Synaptic changes are early manifestations of neuronal dysfunction in Huntington's disease (HD). However, the mechanisms by which mutant HTT protein impacts synaptogenesis and function are not well understood. Herein we explored HD pathogenesis in the BACHD mouse model by examining synaptogenesis and function in long term primary cortical cultures. At DIV14 (days in vitro), BACHD cortical neurons showed no difference from WT neurons in synaptogenesis as revealed by colocalization of a pre-synaptic (Synapsin I) and a post-synaptic (PSD95) marker. From DIV21 to DIV35, BACHD neurons showed progressively reduced colocalization of Synapsin I and PSD95 relative to WT neurons. The deficits were effectively rescued by treatment of BACHD neurons with BDNF. The recombinant apical domain of CCT1 (ApiCCT1) yielded a partial rescuing effect. BACHD neurons also showed culture age-related significant functional deficits as revealed by multielectrode arrays (MEAs). These deficits were prevented by BDNF, whereas ApiCCT1 showed a less potent effect. These findings are evidence that deficits in BACHD synapse and function can be replicated in vitro and that BDNF or a TRiC-inspired reagent can potentially be protective against these changes in BACHD neurons. Our findings support the use of cellular models to further explicate HD pathogenesis and potential treatments.

IST1 regulates select recycling pathways

ESCRTs (Endosomal Sorting Complex Required for Transports) are a modular set of protein complexes with membrane remodeling activities that include the formation and release of intraluminal vesicles (ILVs) to generate multivesicular endosomes. While most of the 12 ESCRT-III proteins are known to play roles in ILV formation, IST1 has been associated with a wider range of endosomal remodeling events. Here, we extend previous studies of IST1 function in endosomal trafficking and confirm that IST1, along with its binding partner CHMP1B, contributes to scission of early endosomal carriers. Functionally, depleting IST1 impaired delivery of transferrin receptor from early/sorting endosomes to the endocytic recycling compartment and instead increased its rapid recycling to the plasma membrane via peripheral endosomes enriched in the clathrin adaptor AP-1. IST1 is also important for export of mannose 6-phosphate receptor from early/sorting endosomes. Examination of IST1 binding partners on endosomes revealed that IST1 interacts with the MIT domain-containing sorting nexin SNX15, a protein previously reported to regulate endosomal recycling. Our kinetic and spatial analyses establish that SNX15 and IST1 occupy a clathrin-containing subdomain on the endosomal perimeter distinct from those previously implicated in cargo retrieval or degradation. Using live-cell microscopy, we see that SNX15 and CHMP1B alternately recruit IST1 to this subdomain or the base of endosomal tubules. These findings indicate that IST1 contributes to a subset of recycling pathways from the early/sorting endosome.

IST1 regulates select endosomal recycling pathways

ESCRTs (Endosomal Sorting Complex Required for Transport) are a modular set of protein complexes with membrane remodeling activities that include the formation and release of intralumenal vesicles (ILVs) to generate multivesicular endosomes. While most of the 12 ESCRT-III proteins are known to play roles in ILV formation, IST1 has been associated with a wider range of endosomal remodeling events. Here, we extend previous studies of IST1 function in endosomal trafficking and confirm that IST1, along with its binding partner CHMP1B, contributes to scission of early endosomal carriers. Depleting IST1 impaired delivery of transferrin receptor from early/sorting endosomes to the endocytic recycling compartment and instead increased its rapid recycling to the plasma membrane via peripheral endosomes enriched in the clathrin adaptor AP-1. IST1 is also important for export of mannose 6-phosphate receptor from early/sorting endosomes. Examination of IST1 binding partners on endosomes revealed that IST1 interacts with the MIT domain-containing sorting nexin SNX15, a protein previously reported to regulate endosomal recycling. Our kinetic and spatial analyses establish that SNX15 and IST1 occupy a clathrin-containing subdomain on the endosomal perimeter distinct from those previously implicated in cargo retrieval or degradation. Using live-cell microscopy we see that SNX15 and CHMP1B alternately recruit IST1 to this subdomain or the base of endosomal tubules. These findings indicate that IST1 contributes to a subset of recycling pathways from the early/sorting endosome.

Quantitative real-time in-cell imaging reveals heterogeneous clusters of proteins prior to condensation

Our current understanding of biomolecular condensate formation is largely based on observing the final near-equilibrium condensate state. Despite expectations from classical nucleation theory, pre-critical protein clusters were recently shown to form under subsaturation conditions in vitro; if similar long-lived clusters comprising more than a few molecules are also present in cells, our understanding of the physical basis of biological phase separation may fundamentally change. Here, we combine fluorescence microscopy with photobleaching analysis to quantify the formation of clusters of NELF proteins in living, stressed cells. We categorise small and large clusters based on their dynamics and their response to p38 kinase inhibition. We find a broad distribution of pre-condensate cluster sizes and show that NELF protein cluster formation can be explained as non-classical nucleation with a surprisingly flat free-energy landscape for a wide range of sizes and an inhibition of condensation in unstressed cells.

Discrete Generalized Inverted Exponential Distribution: Case Study Color Image Segmentation

We present in this paper a discrete analogue of the continuous generalized inverted exponential distribution denoted by discrete generalized inverted exponential (DGIE) distribution. Since, it is cumbersome or difficult to measure a large number of observations in reality on a continuous scale in the area of reliability analysis. Yet, there are a number of discrete distributions in the literature; however, these distributions have certain difficulties in properly fitting a large amount of data in a variety of fields. The presented $\mathbf{DGIE}\left(\beta ,\theta \right)$ has shown the efficiency in fitting data better than some existing distribution. In this study, some basic distributional properties, moments, probability function, reliability indices, characteristic function, and the order statistics of the new DGIE are discussed. Estimation of the parameters is illustrated using the moment's method as well as the maximum likelihood method. Simulations are used to show the performance of the estimated parameters. The model with two real data sets is also examined. In addition, the developed DGIE is applied as color image segmentation which aims to cluster the pixels into their groups. To evaluate the performance of DGIE, a set of six color images is used, as well as it is compared with other image segmentation methods including Gaussian mixture model, K-means, and Fuzzy subspace clustering. The DGIE provides higher performance than other competitive methods.

Stepwise disassembly of GABAergic synapses during pathogenic excitotoxicity

GABAergic synaptic inhibition controls neuronal firing, excitability, and synaptic plasticity to regulate neuronal circuits. Following an acute excitotoxic insult, inhibitory synapses are eliminated, reducing synaptic inhibition, elevating circuit excitability, and contributing to the pathophysiology of brain injuries. However, mechanisms that drive inhibitory synapse disassembly and elimination are undefined. We find that inhibitory synapses are disassembled in a sequential manner following excitotoxicity: GABAARs undergo rapid nanoscale rearrangement and are dispersed from the synapse along with presynaptic active zone components, followed by the gradual removal of the gephyrin scaffold, prior to complete elimination of the presynaptic terminal. GABAAR nanoscale reorganization and synaptic declustering depends on calcineurin signaling, whereas disassembly of gephyrin relies on calpain activation, and blockade of both enzymes preserves inhibitory synapses after excitotoxic insult. Thus, inhibitory synapse disassembly occurs rapidly, with nanoscale precision, in a stepwise manner and most likely represents a critical step in the progression of hyperexcitability following excitotoxicity.

Cell type-specific lipid storage changes in Parkinson's disease patient brains are recapitulated by experimental glycolipid disturbance

Neurons are dependent on proper trafficking of lipids to neighboring glia for lipid exchange and disposal of potentially lipotoxic metabolites, producing distinct lipid distribution profiles among various cell types of the central nervous system. Little is known of the cellular distribution of neutral lipids in the substantia nigra (SN) of Parkinson's disease (PD) patients and its relationship to inflammatory signaling. This study aimed to determine human PD SN neutral lipid content and distribution in dopaminergic neurons, astrocytes, and microglia relative to age-matched healthy subject controls. The results show that while total neutral lipid content was unchanged relative to age-matched controls, the levels of whole SN triglycerides were correlated with inflammation-attenuating glycoprotein non-metastatic melanoma protein B (GPNMB) signaling in human PD SN. Histological localization of neutral lipids using a fluorescent probe (BODIPY) revealed that dopaminergic neurons and midbrain microglia significantly accumulated intracellular lipids in PD SN, while adjacent astrocytes had a reduced lipid load overall. This pattern was recapitulated by experimental in vivo inhibition of glucocerebrosidase activity in mice. Agents or therapies that restore lipid homeostasis among neurons, astrocytes, and microglia could potentially correct PD pathogenesis and disease progression.

Development of Ependymal and Postnatal Neural Stem Cells and Their Origin from a Common Embryonic Progenitor

The adult mouse brain contains an extensive neurogenic niche in the lateral walls of the lateral ventricles. This epithelium, which has a unique pinwheel organization, contains multiciliated ependymal (E1) cells and neural stem cells (B1). This postnatal germinal epithelium develops from the embryonic ventricular zone, but the lineage relationship between E1 and B1 cells remains unknown. Distinct subpopulations of radial glia (RG) cells in late embryonic and early postnatal development either expand their apical domain >11-fold to form E1 cells or retain small apical domains that coalesce into the centers of pinwheels to form B1 cells. Using independent methods of lineage tracing, we show that individual RG cells can give rise to clones containing E1 and B1 cells. This study reveals key developmental steps in the formation of the postnatal germinal niche and the shared cellular origin of E1 and B1 cells.

Nanoscale Subsynaptic Domains Underlie the Organization of the Inhibitory Synapse

Inhibitory synapses mediate the majority of synaptic inhibition in the brain, thereby controlling neuronal excitability, firing, and plasticity. Although essential for neuronal function, the central question of how these synapses are organized at the subsynaptic level remains unanswered. Here, we use three-dimensional (3D) super-resolution microscopy to image key components of the inhibitory postsynaptic domain and presynaptic terminal, revealing that inhibitory synapses are organized into nanoscale subsynaptic domains (SSDs) of the gephyrin scaffold, GABA_ARs and the active-zone protein Rab3-interacting molecule (RIM). Gephyrin SSDs cluster GABA_AR SSDs, demonstrating nanoscale architectural interdependence between scaffold and receptor. GABA_AR SSDs strongly associate with active-zone RIM SSDs, indicating an important role for GABA_AR nanoscale organization near sites of GABA release. Finally, we find that in response to elevated activity, synapse growth is mediated by an increase in the number of postsynaptic SSDs, suggesting a modular mechanism for increasing inhibitory synaptic strength.

Membrane and Actin Tethering Transitions Help IQGAP1 Coordinate GTPase and Lipid Messenger Signaling

The coordination of lipid messenger signaling with cytoskeletal regulation is central to many organelle-specific regulatory processes. This coupling often depends on the function of multidomain scaffolds that orchestrate transient interactions among multiple signaling intermediates and regulatory proteins on organelles. The number of possible scaffold interaction partners and the ability for these interactions to occur at different timescales makes investigations of scaffold functions challenging. This work employs live cell imaging to probe how the multidomain scaffold IQ motif containing GTPase activating protein 1 (IQGAP1) coordinates the activities of proteins affecting local actin polymerization, membrane processing, and phosphoinositide signaling. Using endosomes that are confined by a local actin network as a model system, we demonstrate that IQGAP1 can transition between different actin and endosomal membrane tethered states. Fast scaffold binding/disassociation transitions are shown to be driven by interactions between C-terminal scaffold domains and Rho GTPases at the membrane. Fluctuations in these binding modes are linked to negative regulation of actin polymerization. Although this control governs core elements of IQGAP1 dynamics, actin binding by the N-terminal calponin homology domain of the scaffold is shown to help the scaffold track the temporal development of endosome membrane markers, implying actin associations bolster membrane and actin coordination. Importantly, these effects are not easily distilled purely through standard (static) co-localization analyses or traditional pathway perturbations methods and were resolved by performing dynamic correlation and multiple regression analyses of IQGAP1 scaffold mutants. Using these capabilities with pharmacological inhibition, we provide evidence that membrane tethering is dependent on the activities of the lipid kinase phosphoinositide 3-kinase in addition to the Rho GTPases Rac1 and Cdc42. Overall, these methods and results point to a scaffold tethering mechanism that allows IQGAP1 to help control the amplitude of phosphoinositide lipid messenger signaling by coordinating signaling intermediate activities with the development and disassembly of local actin cytoskeletal networks.

Modeling Point Spread Function in Fluorescence Microscopy With a Sparse Gaussian Mixture: Tradeoff Between Accuracy and Efficiency

Deblurring is a fundamental inverse problem in bioimaging. It requires modeling the point spread function (PSF), which captures the optical distortions entailed by the image formation process. The PSF limits the spatial resolution attainable for a given microscope. However, recent applications require a higher resolution and have prompted the development of super-resolution techniques to achieve sub-pixel accuracy. This requirement restricts the class of suitable PSF models to analog ones. In addition, deblurring is computationally intensive, hence further requiring computationally efficient models. A custom candidate fitting both the requirements is the Gaussian model. However, this model cannot capture the rich tail structures found in both the theoretical and empirical PSFs. In this paper, we aim at improving the reconstruction accuracy beyond the Gaussian model, while preserving its computational efficiency. We introduce a new class of analog PSF models based on the Gaussian mixtures. The number of Gaussian kernels controls both the modeling accuracy and the computational efficiency of the model: the lower the number of kernels, the lower the accuracy and the higher the efficiency. To explore the accuracy-efficiency tradeoff, we propose a variational formulation of the PSF calibration problem, where a convex sparsity-inducing penalty on the number of Gaussian kernels allows trading accuracy for efficiency. We derive an efficient algorithm based on a fully split formulation of alternating split Bregman. We assess our framework on synthetic and real data, and demonstrate a better reconstruction accuracy in both geometry and photometry in point source localization-a fundamental inverse problem in fluorescence microscopy.

Linear Regression Supporting Vector Machine and Hybrid LOG Filter-Based Image Restoration

The image restoration (IR) technique is a part of image processing to improve the quality of an image that is affected by noise and blur. Thus, IR is required to attain a better quality of image. In this paper, IR is performed using linear regression-based support vector machine (LR-SVM). This LR-SVM has two steps: training and testing. The training and testing stages have a distinct windowing process for extracting blocks from the images. The LR-SVM is trained through a block-by-block training sequence. The extracted block-by-block values of images are used to enhance the classification process of IR. In training, the imperfections on the image are easily identified by setting the target vectors as the original images. Then, the noisy image is given at LR-SVM testing, based on the original image restored from the dictionary. Finally, the image block from the testing stage is enhanced using the hybrid Laplacian of Gaussian (HLOG) filter. The denoising of the HLOG filter provides enhanced results by using block-by-block values. This proposed approach is named as LR-SVM-HLOG. A dataset used in this LR-SVM-HLOG method is the Berkeley Segmentation Database. The performance of LR-SVM-HLOG was analyzed as peak signal-to-noise ratio (PSNR) and structural similarity index. The PSNR values of the house and pepper image (color image) are 40.82 and 36.56 dB, respectively, which are higher compared to the inter- and intra-block sparse estimation method and block matching and three-dimensional filtering for color images at 20% noise.

Disruption of mitochondrial dynamics affects behaviour and lifespan in Caenorhabditis elegans

Mitochondria are essential components of eukaryotic cells, carrying out critical physiological processes that include energy production and calcium buffering. Consequently, mitochondrial dysfunction is associated with a range of human diseases. Fundamental to their function is the ability to transition through fission and fusion states, which is regulated by several GTPases. Here, we have developed new methods for the non-subjective quantification of mitochondrial morphology in muscle and neuronal cells of Caenorhabditis elegans. Using these techniques, we uncover surprising tissue-specific differences in mitochondrial morphology when fusion or fission proteins are absent. From ultrastructural analysis, we reveal a novel role for the fusion protein FZO-1/mitofusin 2 in regulating the structure of the inner mitochondrial membrane. Moreover, we have determined the influence of the individual mitochondrial fission (DRP-1/DRP1) and fusion (FZO-1/mitofusin 1,2; EAT-3/OPA1) proteins on animal behaviour and lifespan. We show that loss of these mitochondrial fusion or fission regulators induced age-dependent and progressive deficits in animal movement, as well as in muscle and neuronal function. Our results reveal that disruption of fusion induces more profound defects than lack of fission on animal behaviour and tissue function, and imply that while fusion is required throughout life, fission is more important later in life likely to combat ageing-associated stressors. Furthermore, our data demonstrate that mitochondrial function is not strictly dependent on morphology, with no correlation found between morphological changes and behavioural defects. Surprisingly, we find that disruption of either mitochondrial fission or fusion significantly reduces median lifespan, but maximal lifespan is unchanged, demonstrating that mitochondrial dynamics play an important role in limiting variance in longevity across isogenic populations. Overall, our study provides important new insights into the central role of mitochondrial dynamics in maintaining organismal health.

Enhancing MicroRNA Activity through Increased Endosomal Release Mediated by Nigericin

The therapeutic promise of small-RNA therapeutics is limited, not only by the lack of delivery vehicles, but also by the inability of the small RNAs to reach intracellular compartments where they can be biologically active. We previously reported successful delivery of functionally active miRNAs via receptor-mediated endocytosis. This type of targeted therapy still faces a major challenge in the delivery field: endosomal sequestration. Here, a new method has been developed to promote endosomal escape of delivered miRNA. The strategy relies on the difference in solute contents between nascent endosomes and the cytoplasm; early endosomes are rich in sodium ions, whereas the intracellular fluid is rich is potassium ions. Exploiting this difference through favoring the influx of potassium into the endosomes without the exchange of osmotically active sodium, results in an osmotic differential leading to the endosomes swelling and bursting. One molecule that is able to exchange potassium for an osmotically inactive hydrogen ion is the ionophore nigericin. Through generating an intramolecular miRNA delivery vehicle, containing a ligand, in this case folate and nigericin, we enabled the escape of folate-RNA conjugates from their entrapping endosomes into the cytoplasm where they bound the RNA-induced silencing complex and activated the RNAi response.

Adaptive particle representation of fluorescence microscopy images

Modern microscopes create a data deluge with gigabytes of data generated each second, and terabytes per day. Storing and processing this data is a severe bottleneck, not fully alleviated by data compression. We argue that this is because images are processed as grids of pixels. To address this, we propose a content-adaptive representation of fluorescence microscopy images, the Adaptive Particle Representation (APR). The APR replaces pixels with particles positioned according to image content. The APR overcomes storage bottlenecks, as data compression does, but additionally overcomes memory and processing bottlenecks. Using noisy 3D images, we show that the APR adaptively represents the content of an image while maintaining image quality and that it enables orders of magnitude benefits across a range of image processing tasks. The APR provides a simple and efficient content-aware representation of fluosrescence microscopy images.

AKAP150 Palmitoylation Regulates Synaptic Incorporation of Ca2+-Permeable AMPA Receptors to Control LTP

Ca2+-permeable AMPA-type glutamate receptors (CP-AMPARs) containing GluA1 but lacking GluA2 subunits contribute to multiple forms of synaptic plasticity, including long-term potentiation (LTP), but mechanisms regulating CP-AMPARs are poorly understood. A-kinase anchoring protein (AKAP) 150 scaffolds kinases and phosphatases to regulate GluA1 phosphorylation and trafficking, and trafficking of AKAP150 itself is modulated by palmitoylation on two Cys residues. Here, we developed a palmitoylation-deficient knockin mouse to show that AKAP150 palmitoylation regulates CP-AMPAR incorporation at hippocampal synapses. Using biochemical, super-resolution imaging, and electrophysiological approaches, we found that palmitoylation promotes AKAP150 localization to recycling endosomes and the postsynaptic density (PSD) to limit CP-AMPAR basal synaptic incorporation. In addition, we found that AKAP150 palmitoylation is required for LTP induced by weaker stimulation that recruits CP-AMPARs to synapses but not stronger stimulation that recruits GluA2-containing AMPARs. Thus, AKAP150 palmitoylation controls its subcellular localization to maintain proper basal and activity-dependent regulation of synaptic AMPAR subunit composition.

A Bayesian framework for the analog reconstruction of kymographs from fluorescence microscopy data

Kymographs are widely used to represent and analyse spatio-temporal dynamics of fluorescence markers along curvilinear biological compartments. These objects have a singular geometry, thus kymograph reconstruction is inherently an analog image processing task. However, the existing approaches are essentially digital: the kymograph photometry is sampled directly from the time-lapse images. As a result, such kymographs rely on raw image data that suffer from the degradations entailed by the image formation process and the spatio-temporal resolution of the imaging setup. In this work, we address these limitations and introduce a well-grounded Bayesian framework for the analog reconstruction of kymographs. To handle the movement of the object, we introduce an intrinsic description of kymographs using differential geometry: a kymograph is a photometry defined on a parameter space that is embedded in physical space by a time-varying map that follows the object geometry. We model the kymograph photometry as a Lévy innovation process, a flexible class of non-parametric signal priors. We account for the image formation process using the virtual microscope framework. We formulate a computationally tractable representation of the associated maximum a posteriori problem and solve it using a class of efficient and modular algorithms based on the alternating split Bregman. We assess the performance of our Bayesian framework on synthetic data and apply it to reconstruct the fluorescence dynamics along microtubules in vivo in the budding yeast S. cerevisiae. We demonstrate that our framework allows revealing patterns from single time-lapse data that are invisible on standard digital kymographs.

Virus Control of Trafficking from Sorting Endosomes

The maintenance of cell surface proteins is critical to the ability of a cell to sense and respond to information in its environment. As such, modulation of cell surface composition and receptor trafficking is a potentially important target of control in virus infection. Sorting endosomes (SEs) are control stations regulating the recycling or degradation of internalized plasma membrane proteins. Here we report that human cytomegalovirus (HCMV), a ubiquitous betaherpesvirus, alters the fate of internalized clathrin-independent endocytosis (CIE) cargo proteins, retaining them in virally reprogrammed SEs. We show that the small G protein ARF6 (ADP ribosylation factor 6), a regulator of CIE trafficking, is highly associated with SE membranes relative to uninfected cells. Combined with the observation of accumulated CIE cargo at the SE, these results suggest that infection diminishes the egress of ARF6 and its cargo from the SE. Expression of ubiquitin-specific protease 6 (USP6), also known as TRE17, was sufficient to restore ARF6 and some ARF6 cargo trafficking to the cell surface in infected cells. The USP activity of TRE17 was required to rescue both ARF6 and associated cargo from SE retention in infection. The finding that TRE17 expression does not rescue the trafficking of all CIE cargos retained at SEs in infection suggests that HCMV hijacks the normal sorting machinery and selectively sorts specific cargos into endocytic microdomains that are subject to alternative sorting fates.

Cells maintain their surface composition, take up nutrients, and respond to their environment through the internalization and recycling of cargo at the cell surface through endocytic trafficking pathways. During infection with human cytomegalovirus (HCMV), host endocytic membranes are reorganized into a juxtanuclear structure associated with viral assembly and egress. Less appreciated is the effect of this reorganization on the trafficking of host proteins through the endocytic pathway. We show that HCMV retains internalized cargo and the effector of clathrin-independent endocytosis at sorting endosomes. The retention of some cargo, but not all, was reversed by overexpression of a ubiquitin-specific protease, TRE17. Our results demonstrate that HCMV induces profound reprogramming of endocytic trafficking and influences cargo sorting decisions. Further, our work suggests the presence of a novel ubiquitin-regulated checkpoint for the recycling of cargo from sorting endosome. These findings have important implications for host signaling and immune pathways in the context of HCMV infection.

Identification of Insulin Receptor Splice Variant B in Neurons by in situ Detection in Human Brain Samples

Insulin and its receptor are widely expressed in a variety of tissues throughout the body including liver, adipose tissue, liver and brain. The insulin receptor is expressed as two functionally distinct isoforms, differentiated by a single 12 amino acid exon. The two receptor isoforms, designated IR/A and IR/B, are expressed in a highly tissue and cell specific manner and relative proportions of the different isoforms vary during development, aging and disease states. The high degree of similarity between the two isoforms has prevented detailed studies as differentiation of the two isoforms by traditional immunological methods cannot be achieved. We describe here a new in situ RT-PCR/ FISH assay that allows for the visualization of IR/A and IR/B in tissue along with tissue specific markers. We used this new method to show for the first time that IR/A and IR/B are both expressed in neurons in the adult human brain. Thus, we present a method that enables the investigation of IR/A and IR/B insulin receptor isoform expression in situ in various tissues.

Mapping molecular assemblies with fluorescence microscopy and object-based spatial statistics

Elucidating protein functions and molecular organisation requires to localise precisely single or aggregated molecules and analyse their spatial distributions. We develop a statistical method SODA (Statistical Object Distance Analysis) that uses either micro- or nanoscopy to significantly improve on standard co-localisation techniques. Our method considers cellular geometry and densities of molecules to provide statistical maps of isolated and associated (coupled) molecules. We use SODA with three-colour structured-illumination microscopy (SIM) images of hippocampal neurons, and statistically characterise spatial organisation of thousands of synapses. We show that presynaptic synapsin is arranged in asymmetric triangle with the 2 postsynaptic markers homer and PSD95, indicating a deeper localisation of homer. We then determine stoichiometry and distance between localisations of two synaptic vesicle proteins with 3D-STORM. These findings give insights into the protein organisation at the synapse, and prove the efficiency of SODA to quantitatively assess the geometry of molecular assemblies.

Curvature Filters Efficiently Reduce Certain Variational Energies

In image processing, the rapid approximate solution of variational problems involving generic data-fitting terms is often of practical relevance, for example in real-time applications. Variational solvers based on diffusion schemes or the Euler-Lagrange equations are too slow and restricted in the types of data-fitting terms. Here, we present a filter-based approach to reduce variational energies that contain generic data-fitting terms, but are restricted to specific regularizations. Our approach is based on reducing the regularization part of the variational energy, while guaranteeing non-increasing total energy. This is applicable to regularization-dominated models, where the data-fitting energy initially increases, while the regularization energy initially decreases. We present fast discrete filters for regularizers based on Gaussian curvature, mean curvature, and total variation. These pixel-local filters can be used to rapidly reduce the energy of the full model. We prove the convergence of the resulting iterative scheme in a greedy sense, and we show several experiments to demonstrate applications in image-processing problems involving regularization-dominated variational models.

Simultaneous Tumor Segmentation, Image Restoration, and Blur Kernel Estimation in PET Using Multiple Regularizations

Accurate tumor segmentation from PET images is crucial in many radiation oncology applications. Among others, partial volume effect (PVE) is recognized as one of the most important factors degrading imaging quality and segmentation accuracy in PET. Taking into account that image restoration and tumor segmentation are tightly coupled and can promote each other, we proposed a variational method to solve both problems simultaneously in this study. The proposed method integrated total variation (TV) semi-blind de-convolution and Mumford-Shah segmentation with multiple regularizations. Unlike many existing energy minimization methods using either TV or L₂ regularization, the proposed method employed TV regularization over tumor edges to preserve edge information, and L₂ regularization inside tumor regions to preserve the smooth change of the metabolic uptake in a PET image. The blur kernel was modeled as anisotropic Gaussian to address the resolution difference in transverse and axial directions commonly seen in a clinic PET scanner. The energy functional was rephrased using the Γ-convergence approximation and was iteratively optimized using the alternating minimization (AM) algorithm. The performance of the proposed method was validated on a physical phantom and two clinic datasets with non-Hodgkin's lymphoma and esophageal cancer, respectively. Experimental results demonstrated that the proposed method had high performance for simultaneous image restoration, tumor segmentation and scanner blur kernel estimation. Particularly, the recovery coefficients (RC) of the restored images of the proposed method in the phantom study were close to 1, indicating an efficient recovery of the original blurred images; for segmentation the proposed method achieved average dice similarity indexes (DSIs) of 0.79 and 0.80 for two clinic datasets, respectively; and the relative errors of the estimated blur kernel widths were less than 19% in the transversal direction and 7% in the axial direction.

Joint Segmentation and Deconvolution of Ultrasound Images Using a Hierarchical Bayesian Model Based on Generalized Gaussian Priors

This paper proposes a joint segmentation and deconvolution Bayesian method for medical ultrasound (US) images. Contrary to piecewise homogeneous images, US images exhibit heavy characteristic speckle patterns correlated with the tissue structures. The generalized Gaussian distribution (GGD) has been shown to be one of the most relevant distributions for characterizing the speckle in US images. Thus, we propose a GGD-Potts model defined by a label map coupling US image segmentation and deconvolution. The Bayesian estimators of the unknown model parameters, including the US image, the label map, and all the hyperparameters are difficult to be expressed in a closed form. Thus, we investigate a Gibbs sampler to generate samples distributed according to the posterior of interest. These generated samples are finally used to compute the Bayesian estimators of the unknown parameters. The performance of the proposed Bayesian model is compared with the existing approaches via several experiments conducted on realistic synthetic data and in vivo US images.

Opposing Regulation of the EGF Receptor: A Molecular Switch Controlling Cytomegalovirus Latency and Replication

Herpesviruses persist indefinitely in their host through complex and poorly defined interactions that mediate latent, chronic or productive states of infection. Human cytomegalovirus (CMV or HCMV), a ubiquitous β-herpesvirus, coordinates the expression of two viral genes, UL135 and UL138, which have opposing roles in regulating viral replication. UL135 promotes reactivation from latency and virus replication, in part, by overcoming replication-suppressive effects of UL138. The mechanism by which UL135 and UL138 oppose one another is not known. We identified viral and host proteins interacting with UL138 protein (pUL138) to begin to define the mechanisms by which pUL135 and pUL138 function. We show that pUL135 and pUL138 regulate the viral cycle by targeting that same receptor tyrosine kinase (RTK) epidermal growth factor receptor (EGFR). EGFR is a major homeostatic regulator involved in cellular proliferation, differentiation, and survival, making it an ideal target for viral manipulation during infection. pUL135 promotes internalization and turnover of EGFR from the cell surface, whereas pUL138 preserves surface expression and activation of EGFR. We show that activated EGFR is sequestered within the infection-induced, juxtanuclear viral assembly compartment and is unresponsive to stress. Intriguingly, these findings suggest that CMV insulates active EGFR in the cell and that pUL135 and pUL138 function to fine-tune EGFR levels at the cell surface to allow the infected cell to respond to extracellular cues. Consistent with the role of pUL135 in promoting replication, inhibition of EGFR or the downstream phosphoinositide 3-kinase (PI3K) favors reactivation from latency and replication. We propose a model whereby pUL135 and pUL138 together with EGFR comprise a molecular switch that regulates states of latency and replication in HCMV infection by regulating EGFR trafficking to fine tune EGFR signaling.

Cytomegalovirus, a herpesvirus, persists in its host through complex interactions that mediate latent, chronic or productive states of infection. Defining the mechanistic basis viral persistence is important for defining the costs and possible benefits of viral persistence and to mitigate pathologies associated with reactivation. We have identified two genes, UL135 and UL138, with opposing roles in regulating states of latency and replication. UL135 promotes replication and reactivation from latency, in part, by overcoming suppressive effects of UL138. Intriguingly, pUL135 and pUL138 regulate the viral cycle by targeting the same receptor tyrosine kinase, epidermal growth factor receptor (EGFR). EGFR is a major homeostatic regulator controlling cellular proliferation, differentiation, and survival, making it an ideal target for viruses to manipulate during infection. We show that CMV insulates and regulates EGFR levels and activity by modulating its trafficking. This work defines a molecular switch that regulates latent and replicative states of infection through the modulation of host trafficking and signaling pathways. The regulation of EGFR at the cell surface provides a novel means by which the virus may sense and respond to changes in the host environment to enter into or exit the latent state.

A Parallel Distributed-Memory Particle Method Enables Acquisition-Rate Segmentation of Large Fluorescence Microscopy Images

Modern fluorescence microscopy modalities, such as light-sheet microscopy, are capable of acquiring large three-dimensional images at high data rate. This creates a bottleneck in computational processing and analysis of the acquired images, as the rate of acquisition outpaces the speed of processing. Moreover, images can be so large that they do not fit the main memory of a single computer. We address both issues by developing a distributed parallel algorithm for segmentation of large fluorescence microscopy images. The method is based on the versatile Discrete Region Competition algorithm, which has previously proven useful in microscopy image segmentation. The present distributed implementation decomposes the input image into smaller sub-images that are distributed across multiple computers. Using network communication, the computers orchestrate the collectively solving of the global segmentation problem. This not only enables segmentation of large images (we test images of up to 10(10) pixels), but also accelerates segmentation to match the time scale of image acquisition. Such acquisition-rate image segmentation is a prerequisite for the smart microscopes of the future and enables online data compression and interactive experiments.

Subcellular object quantification with Squassh3C and SquasshAnalyst

Quantitative image analysis plays an important role in contemporary biomedical research. Squassh is a method for automatic detection, segmentation, and quantification of subcellular structures and analysis of their colocalization. Here we present the applications Squassh3C and SquasshAnalyst. Squassh3C extends the functionality of Squassh to three fluorescence channels and live-cell movie analysis. SquasshAnalyst is an interactive web interface for the analysis of Squassh3C object data. It provides segmentation image overview and data exploration, figure generation, object and image filtering, and a statistical significance test in an easy-to-use interface. The overall procedure combines the Squassh3C plug-in for the free biological image processing program ImageJ and a web application working in conjunction with the free statistical environment R, and it is compatible with Linux, MacOS X, or Microsoft Windows. Squassh3C and SquasshAnalyst are available for download at www.psi.ch/lbr/SquasshAnalystEN/SquasshAnalyst.zip.

Intracellular trafficking of AIP56, an NF-κB-cleaving toxin from Photobacterium damselae subsp. piscicida

AIP56 (apoptosis-inducing protein of 56 kDa) is a metalloprotease AB toxin secreted by Photobacterium damselae subsp. piscicida that acts by cleaving NF-κB. During infection, AIP56 spreads systemically and depletes phagocytes by postapoptotic secondary necrosis, impairing the host phagocytic defense and contributing to the genesis of infection-associated necrotic lesions. Here we show that mouse bone marrow-derived macrophages (mBMDM) intoxicated by AIP56 undergo NF-κB p65 depletion and apoptosis. Similarly to what was reported for sea bass phagocytes, intoxication of mBMDM involves interaction of AIP56 C-terminal region with cell surface components, suggesting the existence of a conserved receptor. Biochemical approaches and confocal microscopy revealed that AIP56 undergoes clathrin-dependent endocytosis, reaches early endosomes, and follows the recycling pathway. Translocation of AIP56 into the cytosol requires endosome acidification, and an acidic pulse triggers translocation of cell surface-bound AIP56 into the cytosol. Accordingly, at acidic pH, AIP56 becomes more hydrophobic, interacting with artificial lipid bilayer membranes. Altogether, these data indicate that AIP56 is a short-trip toxin that reaches the cytosol using an acidic-pH-dependent mechanism, probably from early endosomes. Usually, for short-trip AB toxins, a minor pool reaches the cytosol by translocating from endosomes, whereas the rest is routed to lysosomes for degradation. Here we demonstrate that part of endocytosed AIP56 is recycled back and released extracellularly through a mechanism requiring phosphoinositide 3-kinase (PI3K) activity but independent of endosome acidification. So far, we have been unable to detect biological activity of recycled AIP56, thereby bringing into question its biological relevance as well as the importance of the recycling pathway.

MosaicIA: an ImageJ/Fiji plugin for spatial pattern and interaction analysis

Background

Analyzing spatial distributions of objects in images is a fundamental task in many biological studies. The relative arrangement of a set of objects with respect to another set of objects contains information about potential interactions between the two sets of objects. If they do not “feel” each other’s presence, their spatial distributions are expected to be independent of one another. Spatial correlations in their distributions are indicative of interactions and can be modeled by an effective interaction potential acting between the points of the two sets. This can be used to generalize co-localization analysis to spatial interaction analysis. However, no user-friendly software for this type of analysis was available so far.

Results

We present an ImageJ/Fiji plugin that implements the complete workflow of spatial pattern and interaction analysis for spot-like objects. The plugin detects objects in images, infers the interaction potential that is most likely to explain the observed pattern, and provides statistical tests for whether an inferred interaction is significant given the number of objects detected in the images and the size of the space within which they can distribute. We benchmark and demonstrate the present software using examples from confocal and PALM single-molecule microscopy.

Conclusions

The present software greatly simplifies spatial interaction analysis for point patterns, and makes it available to the large user community of ImageJ and Fiji. The presented showcases illustrate the usage of the software.