Differential effects of FcRn antagonists on the subcellular trafficking of FcRn and albumin.

The homeostasis of IgG is maintained by the neonatal Fc receptor, FcRn. Consequently, antagonism of FcRn to reduce endogenous IgG levels is an emerging strategy for treating antibody-mediated autoimmune disorders using either FcRn-specific antibodies or an engineered Fc fragment. For certain FcRn-specific antibodies, this approach has resulted in reductions in the levels of serum albumin, the other major ligand transported by FcRn. Cellular and molecular analyses of a panel of FcRn antagonists have been carried out to elucidate the mechanisms leading to their differential effects on albumin homeostasis. These analyses have identified 2 processes underlying decreases in albumin levels during FcRn blockade: increased degradation of FcRn and competition between antagonist and albumin for FcRn binding. These findings have potential implications for the design of drugs to modulate FcRn function.

Selective depletion of radiolabeled HER2-specific antibody for contrast improvement during PET.

The prolonged in vivo persistence of antibodies results in high background and poor contrast during their use as molecular imaging agents for positron emission tomography (PET). We have recently described a class of engineered Fc fusion proteins that selectively deplete antigen-specific antibodies without affecting the levels of antibodies of other specificities. Here, we demonstrate that these Fc fusions (called Seldegs, for selective degradation) can be used to clear circulating, radiolabeled HER2-specific antibody during diagnostic imaging of HER2-positive tumors in mice. The analyses show that Seldegs have considerable promise for the reduction of whole-body exposure to radiolabel and improvement of contrast during PET.

Effect of Pixelation on the Parameter Estimation of Single Molecule Trajectories.

The advent of single molecule microscopy has revolutionized biological investigations by providing a powerful tool for the study of intercellular and intracellular trafficking processes of protein molecules which was not available before through conventional microscopy. In practice, pixelated detectors are used to acquire the images of fluorescently labeled objects moving in cellular environments. Then, the acquired fluorescence microscopy images contain the numbers of the photons detected in each pixel, during an exposure time interval. Moreover, instead of having the exact locations of detection of the photons, we only know the pixel areas in which the photons impact the detector. These challenges make the analysis of single molecule trajectories, from pixelated images, a complex problem. Here, we investigate the effect of pixelation on the parameter estimation of single molecule trajectories. In particular, we develop a stochastic framework to calculate the maximum likelihood estimates of the parameters of a stochastic differential equation that describes the motion of the molecule in living cells. We also calculate the Fisher information matrix for this parameter estimation problem. The analytical results are complicated through the fact that the observation process in a microscope prohibits the use of standard Kalman filter type approaches. The analytical framework presented here is illustrated with examples of low photon count scenarios for which we rely on Monte Carlo methods to compute the associated probability distributions.

Microscope calibration protocol for single-molecule microscopy.

Single-molecule microscopy allows for the investigation of the dynamics of individual molecules and the visualization of subcellular structures at high spatial resolution. For single-molecule imaging experiments, and particularly those that entail the acquisition of multicolor data, calibration of the microscope and its optical components therefore needs to be carried out at a high level of accuracy. We propose here a method for calibrating a microscope at the nanometer scale, in the sense of determining optical aberrations as revealed by point source localization errors on the order of nanometers. The method is based on the imaging of a standard sample to detect and evaluate the amount of geometric aberration introduced in the optical light path. To provide support for multicolor imaging, it also includes procedures for evaluating the geometric aberration caused by a dichroic filter and the axial chromatic aberration introduced by an objective lens.

Selective Depletion of Antigen-Specific Antibodies for the Treatment of Demyelinating Disease.

Current treatments for antibody-mediated autoimmunity are associated with lack of specificity, leading to immunosuppressive effects. To overcome this limitation, we have developed a class of antibody-based therapeutics for the treatment of autoimmunity involving antibodies that recognize the autoantigen, myelin oligodendrocyte glycoprotein (MOG). These agents ("Seldegs," for selective degradation) selectively eliminate antigen (MOG)-specific antibodies without affecting the levels of antibodies of other specificities. Seldeg treatment of mice during antibody-mediated exacerbation of experimental autoimmune encephalomyelitis by patient-derived MOG-specific antibodies results in disease amelioration. Consistent with their therapeutic effects, Seldegs deliver their targeted antibodies to Kupffer and liver sinusoidal endothelial cells that are known to have tolerogenic effects. Our results show that Seldegs can ameliorate disease mediated by MOG-specific antibodies and indicate that this approach also has the potential to treat other autoimmune diseases where the specific clearance of antibodies is required.

A two-stage method for automated detection of ring-like endosomes in fluorescent microscopy images.

Endosomes are subcellular organelles which serve as important transport compartments in eukaryotic cells. Fluorescence microscopy is a widely applied technology to study endosomes at the subcellular level. In general, a microscopy image can contain a large number of organelles and endosomes in particular. Detecting and annotating endosomes in fluorescence microscopy images is a critical part in the study of subcellular trafficking processes. Such annotation is usually performed by human inspection, which is time-consuming and prone to inaccuracy if carried out by inexperienced analysts. This paper proposes a two-stage method for automated detection of ring-like endosomes. The method consists of a localization stage cascaded by an identification stage. Given a test microscopy image, the localization stage generates a voting-map by locally comparing the query endosome patches and the test image based on a bag-of-words model. Using the voting-map, a number of candidate patches of endosomes are determined. Subsequently, in the identification stage, a support vector machine (SVM) is trained using the endosome patches and the background pattern patches. Each of the candidate patches is classified by the SVM to rule out those patches of endosome-like background patterns. The performance of the proposed method is evaluated with real microscopy images of human myeloid endothelial cells. It is shown that the proposed method significantly outperforms several state-of-the-art competing methods using multiple performance metrics.

Publisher Correction: Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software.

In the version of this paper originally published, Figure 4a contained errors that were introduced during typesetting. The bottom 11° ThunderSTORM image is an xz view but was incorrectly labeled as xy, and the low x-axis value in the four line profiles was incorrectly set as -60 instead of -50. These errors have been corrected in the PDF and HTML versions of the paper.

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software.

With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3D SMLM software packages. We generated realistic simulated datasets for popular imaging modalities-2D, astigmatic 3D, biplane 3D and double-helix 3D-and evaluated 36 participant packages against these data. This provides the first broad assessment of 3D SMLM software and provides a holistic view of how the latest 2D and 3D SMLM packages perform in realistic conditions. This resource allows researchers to identify optimal analytical software for their experiments, allows 3D SMLM software developers to benchmark new software against the current state of the art, and provides insight into the current limits of the field.

Neonatal Fc receptor expression in macrophages is indispensable for IgG homeostasis.

The maintenance of the homeostasis of immunoglobulin G (IgG) represents a fundamental aspect of humoral immunity that has direct relevance to the successful delivery of antibody-based therapeutics. The ubiquitously expressed neonatal Fc receptor (FcRn) salvages IgG from cellular degradation following pinocytic uptake into cells, conferring prolonged in vivo persistence on IgG. However, the cellular sites of FcRn function are poorly defined. Pinocytic uptake is a prerequisite for FcRn-mediated IgG salvage, prompting us to investigate the consequences of IgG uptake and catabolism by macrophages, which represent both abundant and highly pinocytic cells in the body. Site-specific deletion of FcRn to generate mice harboring FcRn-deficient macrophages results in IgG hypercatabolism and ~threefold reductions in serum IgG levels, whereas these effects were not observed in mice that lack functional FcRn in B cells and dendritic cells. Consistent with the degradative activity of FcRn-deficient macrophages, depletion of these cells in FcRn-deficient mice leads to increased persistence and serum levels of IgG. These studies demonstrate a pivotal role for FcRn-mediated salvage in compensating for the high pinocytic and degradative activities of macrophages to maintain IgG homeostasis.

Engineering a HER2-specific antibody-drug conjugate to increase lysosomal delivery and therapeutic efficacy.

We improve the potency of antibody-drug conjugates (ADCs) containing the human epidermal growth factor receptor 2 (HER2)-specific antibody pertuzumab by substantially reducing their affinity for HER2 at acidic endosomal pH relative to near neutral pH. These engineered pertuzumab variants show increased lysosomal delivery and cytotoxicity towards tumor cells expressing intermediate HER2 levels. In HER2int xenograft tumor models in mice, the variants show higher therapeutic efficacy than the parent ADC and a clinically approved HER2-specific ADC.

Resolution limit of image analysis algorithms.

The resolution of an imaging system is a key property that, despite many advances in optical imaging methods, remains difficult to define and apply. Rayleigh's and Abbe's resolution criteria were developed for observations with the human eye. However, modern imaging data is typically acquired on highly sensitive cameras and often requires complex image processing algorithms to analyze. Currently, no approaches are available for evaluating the resolving capability of such image processing algorithms that are now central to the analysis of imaging data, particularly location-based imaging data. Using methods of spatial statistics, we develop a novel algorithmic resolution limit to evaluate the resolving capabilities of location-based image processing algorithms. We show how insufficient algorithmic resolution can impact the outcome of location-based image analysis and present an approach to account for algorithmic resolution in the analysis of spatial location patterns.

A HIDDEN MARKOV MODEL APPROACH TO CHARACTERIZING THE PHOTO-SWITCHING BEHAVIOR OF FLUOROPHORES.

Fluorescing molecules (fluorophores) that stochastically switch between photon-emitting and dark states underpin some of the most celebrated advancements in super-resolution microscopy. While this stochastic behavior has been heavily exploited, full characterization of the underlying models can potentially drive forward further imaging methodologies. Under the assumption that fluorophores move between fluorescing and dark states as continuous time Markov processes, the goal is to use a sequence of images to select a model and estimate the transition rates. We use a hidden Markov model to relate the observed discrete time signal to the hidden continuous time process. With imaging involving several repeat exposures of the fluorophore, we show the observed signal depends on both the current and past states of the hidden process, producing emission probabilities that depend on the transition rate parameters to be estimated. To tackle this unusual coupling of the transition and emission probabilities, we conceive transmission (transition-emission) matrices that capture all dependencies of the model. We provide a scheme of computing these matrices and adapt the forward-backward algorithm to compute a likelihood which is readily optimized to provide rate estimates. When confronted with several model proposals, combining this procedure with the Bayesian Information Criterion provides accurate model selection.

Targeting FcRn to Generate Antibody-Based Therapeutics.

The MHC class I-related receptor FcRn serves multiple roles ranging from the regulation of levels of IgG isotype antibodies and albumin throughout the body to the delivery of antigen into antigen loading compartments in specialized antigen-presenting cells. In parallel with studies directed towards understanding FcRn at the molecular and cellular levels, there has been an enormous expansion in the development of engineering strategies involving FcRn to modulate the dynamic behavior of antibodies, antigens, and albumin. In this review article, we focus on a discussion of FcRn-targeted approaches that have resulted in the production of novel antibody-based platforms with considerable potential for use in the clinic.

Neonatal Fc receptor antagonist efgartigimod safely and sustainably reduces IgGs in humans.

BACKGROUND: Intravenous Ig (IVIg), plasma exchange, and immunoadsorption are frequently used in the management of severe autoimmune diseases mediated by pathogenic IgG autoantibodies. These approaches modulating IgG levels can, however, be associated with some severe adverse reactions and a substantial burden to patients. Targeting the neonatal Fc receptor (FcRn) presents an innovative and potentially more effective, safer, and more convenient alternative for clearing pathogenic IgGs. METHODS: A randomized, double-blind, placebo-controlled first-in-human study was conducted in 62 healthy volunteers to explore single and multiple ascending intravenous doses of the FcRn antagonist efgartigimod. The study objectives were to assess safety, tolerability, pharmacokinetics, pharmacodynamics, and immunogenicity. The findings of this study were compared with the pharmacodynamics profile elicited by efgartigimod in cynomolgus monkeys. RESULTS: Efgartigimod treatment resulted in a rapid and specific clearance of serum IgG levels in both cynomolgus monkeys and healthy volunteers. In humans, single administration of efgartigimod reduced IgG levels up to 50%, while multiple dosing further lowered IgGs on average by 75% of baseline levels. Approximately 8 weeks following the last administration, IgG levels returned to baseline. Efgartigimod did not alter the homeostasis of albumin or Igs other than IgG, and no serious adverse events related to efgartigimod infusion were observed. CONCLUSION: Antagonizing FcRn using efgartigimod is safe and results in a specific, profound, and sustained reduction of serum IgG levels. These results warrant further evaluation of this therapeutic approach in IgG-driven autoimmune diseases. TRIAL REGISTRATION: Clinicaltrials.gov NCT03457649. FUNDING: argenx BVBA.

Phagocytosis of antibody-opsonized tumor cells leads to the formation of a discrete vacuolar compartment in macrophages.

Despite the rapidly expanding use of antibody-based therapeutics to treat cancer, knowledge of the cellular processes following phagocytosis of antibody-opsonized tumor cells is limited. Here we report the formation of a phagosome-associated vacuole that is observed in macrophages as these degradative compartments mature following phagocytosis of HER2-positive cancer cells in the presence of the HER2-specific antibody, trastuzumab. We demonstrate that this vacuole is a distinct organelle that is closely apposed to the phagosome. Furthermore, the size of the phagosome-associated vacuole is increased by inhibition of the mTOR pathway. Collectively, the identification of this vacuolar compartment has implications for understanding the subcellular trafficking processes leading to the destruction of phagocytosed, antibody-opsonized cancer cells by macrophages.

Targeting Phosphatidylserine with Calcium-Dependent Protein-Drug Conjugates for the Treatment of Cancer.

In response to cellular stress, phosphatidylserine is exposed on the outer membrane leaflet of tumor blood vessels and cancer cells, motivating the development of phosphatidylserine-specific therapies. The generation of drug-conjugated phosphatidylserine-targeting agents represents an unexplored therapeutic approach, for which antitumor effects are critically dependent on efficient internalization and lysosomal delivery of the cytotoxic drug. In the current study, we have generated phosphatidylserine-targeting agents by fusing phosphatidylserine-binding domains to a human IgG1-derived Fc fragment. The tumor localization and pharmacokinetics of several phosphatidylserine-specific Fc fusions have been analyzed in mice and demonstrate that Fc-Syt1, a fusion containing the synaptotagmin 1 C2A domain, effectively targets tumor tissue. Conjugation of Fc-Syt1 to the cytotoxic drug monomethyl auristatin E results in a protein-drug conjugate (PDC) that is internalized into target cells and, due to the Ca2+ dependence of phosphatidylserine binding, dissociates from phosphatidylserine in early endosomes. The released PDC is efficiently delivered to lysosomes and has potent antitumor effects in mouse xenograft tumor models. Interestingly, although an engineered, tetravalent Fc-Syt1 fusion shows increased binding to target cells, this higher avidity variant demonstrates reduced persistence and therapeutic effects compared with bivalent Fc-Syt1. Collectively, these studies show that finely tuned, Ca2+-switched phosphatidylserine-targeting agents can be therapeutically efficacious. Mol Cancer Ther; 17(1); 169-82. ©2017 AACR.

Myelin oligodendrocyte glycoprotein-specific antibodies from multiple sclerosis patients exacerbate disease in a humanized mouse model.

Myelin oligodendrocyte glycoprotein (MOG) is exposed on the outer surface of the myelin sheath, and as such, represents a possible target antigen for antibodies in multiple sclerosis (MS) and other demyelinating diseases. However, despite extensive analyses, whether MOG-specific antibodies contribute to pathogenesis in human MS remains an area of uncertainty. In the current study we demonstrate that antibodies derived from adult MS patients exacerbate experimental autoimmune encephalomyelitis (EAE) in 'humanized' mice that transgenically express human FcγRs (hFcγRs). Importantly, this exacerbation is dependent on MOG recognition by the human-derived antibodies. The use of mice that express hFcγRs has allowed us to also investigate the contribution of these receptors to disease in the absence of confounding effects of cross-species differences. Specifically, by engineering the Fc region of MOG-specific antibodies to modulate FcγR and complement (C1q) binding, we reveal that FcγRs but not complement activation contribute to EAE pathogenesis. Importantly, selective enhancement of the affinities of these antibodies for specific FcγRs reveals that FcγRIIA is more important than FcγRIIIA in mediating disease exacerbation. These studies not only provide definitive evidence for the contribution of MOG-specific antibodies to MS, but also reveal mechanistic insight that could lead to new therapeutic targets.

A state space based approach to localizing single molecules from multi-emitter images.

Single molecule super-resolution microscopy is a powerful tool that enables imaging at sub-diffraction-limit resolution. In this technique, subsets of stochastically photoactivated fluorophores are imaged over a sequence of frames and accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Available localization methods typically first determine the regions of the image that contain emitting fluorophores through a process referred to as detection. Then, the locations of the fluorophores are estimated accurately in an estimation step. We propose a novel localization method which combines the detection and estimation steps. The method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix, and determines the locations of intensity peaks in the image as the pole locations of the resulting system. The locations of the most significant peaks correspond to the locations of single molecules in the original image. Although the accuracy of the location estimates is reasonably good, we demonstrate that, by using the estimates as the initial conditions for a maximum likelihood estimator, refined estimates can be obtained that have a standard deviation close to the Cramér-Rao lower bound-based limit of accuracy. We validate our method using both simulated and experimental multi-emitter images.

State space approach to single molecule localization in fluorescence microscopy.

Single molecule super-resolution microscopy enables imaging at sub-diffraction-limit resolution by producing images of subsets of stochastically photoactivated fluorophores over a sequence of frames. In each frame of the sequence, the fluorophores are accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Many methods have been developed for localizing fluorophores from the images. The majority of these methods comprise two separate steps: detection and estimation. In the detection step, fluorophores are identified. In the estimation step, the locations of the identified fluorophores are estimated through an iterative approach. Here, we propose a non-iterative state space-based localization method which combines the detection and estimation steps. We demonstrate that the estimated locations obtained from the proposed method can be used as initial conditions in an estimation routine to potentially obtain improved location estimates. The proposed method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix. The locations of the poles of the resulting system determine the peak locations in the frequency domain, and the locations of the most significant peaks correspond to the single molecule locations in the original image. The performance of the method is validated using both simulated and experimental data.