Dectin-1 multimerization and signaling depends on fungal ß-glucan structure and exposure.

Dectin-1A is a C-type lectin innate immunoreceptor that recognizes ß-(1,3;1,6)-glucan, a structural component of Candida species cell walls. ß-Glucans can adopt solution structures ranging from random coil to insoluble fiber due to tertiary (helical) and quaternary structure. Fungal ß-glucans of medium and high molecular weight are highly structured, but low molecular weight glucan is much less structured. Despite similar affinity for Dectin-1, the ability of glucans to induce Dectin-1A-mediated signaling correlates with degree of structure. Glucan denaturation experiments showed that glucan structure determines agonistic potential, but not receptor binding affinity. We explored the impact of glucan structure on molecular aggregation of Dectin-1A. Stimulation with glucan signaling decreased Dectin-1A diffusion coefficient. Fluorescence measurements provided direct evidence of ligation-induced Dectin-1A aggregation, which positively correlated with increasing glucan structure content. In contrast, Dectin-1A is predominantly in a low aggregation state in resting cells. Molecular aggregates formed during interaction with highly structured, agonistic glucans did not exceed relatively small (<15 nm) clusters of a few engaged receptors. Finally, we observed increased molecular aggregation of Dectin-1A at fungal particle contact sites in a manner that positively correlated with the degree of exposed glucan on the particle surface. These results indicate that Dectin-1A senses the solution conformation of ß-glucans through their varying ability to drive receptor dimer/oligomer formation and activation of membrane proximal signaling events.

RMSD and Symmetry.

A common approach for comparing the structures of biomolecules or solid bodies is to translate and rotate one structure with respect to the other to minimize the pointwise root-mean-square deviation (RMSD). We present a new, robust numerical algorithm that computes the RMSD between two molecules or all the mutual RMSDs of a list of molecules and, if desired, the corresponding rotation matrix in a minimal number of operations as compared to previous algorithms. The RMSD gradient can also be computed. We address the problem of symmetry, both in alignment (possible alternative alignments due to indistinguishable atoms) as well as geometry. In the latter case, it is possible to have degenerate superposition. A necessary condition is optimal superimposability to one's mirror image. Double (respectively, triple) degeneracy results in a one- (respectively, two)-parameter family of rotations leaving the superposition invariant. The software, frmsd, is freely available at http://www.ams.stonybrook.edu/~coutsias/codes/frmsd.tgz. © 2019 Wiley Periodicals, Inc.

A new tool to quantify receptor recruitment to cell contact sites during host-pathogen interaction.

To understand the process of innate immune fungal recognition, we developed computational tools for the rigorous quantification and comparison of receptor recruitment and distribution at cell-cell contact sites. We used these tools to quantify pattern recognition receptor spatiotemporal distributions in contacts between primary human dendritic cells and the fungal pathogens C. albicans, C. parapsilosis and the environmental yeast S. cerevisiae, imaged using 3D multichannel laser scanning confocal microscopy. The detailed quantitative analysis of contact sites shows that, despite considerable biochemical similarity in the composition and structure of these species' cell walls, the receptor spatiotemporal distribution in host-microbe contact sites varies significantly between these yeasts. Our findings suggest a model where innate immune cells discriminate fungal microorganisms based on differential mobilization and coordination of receptor networks. Our analysis methods are also broadly applicable to a range of cell-cell interactions central to many biological problems.

Multiparatopic antibodies induce targeted downregulation of programmed death-ligand 1.

Programmed death-ligand 1 (PD-L1) drives inhibition of antigen-specific T cell responses through engagement of its receptor programmed death-1 (PD-1) on activated T cells. Overexpression of these immune checkpoint proteins in the tumor microenvironment has motivated the design of targeted antibodies that disrupt this interaction. Despite clinical success of these antibodies, response rates remain low, necessitating novel approaches to enhance performance. Here, we report the development of antibody fusion proteins that block immune checkpoint pathways through a distinct mechanism targeting molecular trafficking. By engaging multiple receptor epitopes on PD-L1, our engineered multiparatopic antibodies induce rapid clustering, internalization, and degradation in an epitope- and topology-dependent manner. The complementary mechanisms of ligand blockade and receptor downregulation led to more durable immune cell activation and dramatically reduced PD-L1 availability in mouse tumors. Collectively, these multiparatopic antibodies offer mechanistic insight into immune checkpoint protein trafficking and how it may be manipulated to reprogram immune outcomes.

Antigen Geometry Tunes Mast Cell Signaling Through Distinct FcεRI Aggregation and Structural Changes.

Immunoreceptor tyrosine-based activation motif (ITAM)-containing Fc receptors are critical components of the innate and adaptive immune systems. FcεRI mediates the allergic response via crosslinking of IgE-bound receptors by multivalent antigens. Yet, the underlying molecular mechanisms that govern the response of FcεRI to specific antigens remain poorly understood. We compared responses induced by two antigens with distinct geometries, high valency DNP-BSA and trivalent DF3, and found unique secretion and receptor phosphorylation profiles that are due to differential recruitment of Lyn and SHIP1. To understand how these two antigens can cause such markedly different outcomes, we used direct stochastic optical reconstruction microscopy (dSTORM) super-resolution imaging combined with Bayesian Grouping of Localizations (BaGoL) analysis to compare the nanoscale characteristics of FcεRI aggregates. DF3 aggregates were found to be smaller and more densely packed than DNP-BSA aggregates. Using lifetime-based Förster resonance energy transfer (FRET) measurements, we discovered that FcεRI subunits undergo structural rearrangements upon crosslinking with either antigen, and in response to interaction with monovalent antigen presented on a supported lipid bilayer. The extent of conformational change is positively correlated with signaling efficiency. Finally, we provide evidence for forces in optimizing FcεRI signaling, such that immobilizing DF3 on a rigid surface promoted degranulation while increasing DNP-BSA flexibility lowered degranulation. These results provide a link between the physical attributes of allergens, including size, shape, valency, and flexibility, and FcεRI signaling strength. Thus, the antigen modulates mast cell outcomes by creating unique aggregate geometries that tune FcεRI conformation, phosphorylation and signaling partner recruitment.

SMITE: Single Molecule Imaging Toolbox Extraordinaire (MATLAB).

Fluorescence single molecule imaging comprises a variety of techniques that involve detecting individual fluorescent molecules. Many of these techniques involve localizing individual fluorescent molecules with precisions below the diffraction limit, which limits the spatial resolution of (visible) light-based microscopes. These methodologies are widely used to image biological structures at the nanometer scale by fluorescently tagging the structures of interest, elucidating details of the biological behavior observed. Two common techniques are single-molecule localization microscopy (SMLM), (Betzig et al., 2006; Fazel & Wester, 2022; Hell, 2007; Lidke et al., 2005; Rust et al., 2006; van de Linde et al., 2011) which is used to produce 2D or 3D super-resolution images of static or nearly static structures, and single-particle tracking (SPT) (Shen et al., 2017), which follows the time course of one or a very small number of moving tagged molecules. SMLM often involves distributions of particles at medium to high density, while SPT works in a very low density domain. These procedures all require intensive numerical computation, and the methods are tightly interwoven.

Insights into cell membrane microdomain organization from live cell single particle tracking of the IgE high affinity receptor FcϵRI of mast cells.

Current models propose that the plasma membrane of animal cells is composed of heterogeneous and dynamic microdomains known variously as cytoskeletal corrals, lipid rafts and protein islands. Much of the experimental evidence for these membrane compartments is indirect. Recently, live cell single particle tracking studies using quantum dot-labeled IgE bound to its high affinity receptor FcϵRI, provided direct evidence for the confinement of receptors within micrometer-scale cytoskeletal corrals. In this study, we show that an innovative time-series analysis of single particle tracking data for the high affinity IgE receptor, FcϵRI, on mast cells provides substantial quantitative information about the submicrometer organization of the membrane. The analysis focuses on the probability distribution function of the lengths of the jumps in the positions of the quantum dots labeling individual IgE FcϵRI complexes between frames in movies of their motion. Our results demonstrate the presence, within the micrometer-scale cytoskeletal corrals, of smaller subdomains that provide an additional level of receptor confinement. There is no characteristic size for these subdomains; their size varies smoothly from a few tens of nanometers to a over a hundred nanometers. In QD-IGE labeled unstimulated cells, jumps of less than 70 nm predominate over longer jumps. Addition of multivalent antigen to crosslink the QD-IgE-FcϵRI complexes causes a rapid slowing of receptor motion followed by a long tail of mostly jumps less than 70 nm. The reduced receptor mobility likely reflects both the membrane heterogeneity revealed by the confined motion of the monomeric receptor complexes and the antigen-induced cross linking of these complexes into dimers and higher oligomers. In both cases, the probability distribution of the jump lengths is well fit, from 10 nm to over 100 nm, by a novel power law. The fit for short jumps suggests that the motion of the quantum dots can be modeled as diffusion in a fractal space of dimension less than two.

Modeling the Cluster Size Distribution of Vascular Endothelial Growth Factor (VEGF) Receptors.

We previously developed a method of defining receptor clusters in the membrane based on mutual distance and applied it to a set of transmission microscopy images of vascular endothelial growth factor receptors. An optimal length parameter was identified, resulting in cluster identification and a procedure that assigned a geometric shape to each cluster. We showed that the observed particle distribution results were consistent with the random placement of receptors within the clusters and, to a lesser extent, the random placement of the clusters on the cell membrane. Here, we develop and validate a stochastic model of clustering, based on a hypothesis of preexisting domains that have a high affinity for receptors. The proximate objective is to clarify the mechanism behind cluster formation and to estimate the effect on signaling. Receptor-enriched domains may significantly impact signaling pathways that rely on ligand-induced dimerization of receptors. We define a simple statistical model, based on the preexisting domain hypothesis, to predict the probability distribution of cluster sizes. The process yielded sets of parameter values that can readily be used in dynamical calculations as the estimates of the quantitative characteristics of the clustering domains.

An Optimized Single-Molecule Pull-Down Assay for Quantification of Protein Phosphorylation.

Phosphorylation is a necessary posttranslational modification that regulates protein function and directs cell signaling outcomes. Current methods to measure protein phosphorylation cannot preserve the heterogeneity in phosphorylation across individual proteins. The single-molecule pull-down (SiMPull) assay was developed to investigate the composition of macromolecular complexes via immunoprecipitation of proteins on a glass coverslip followed by single-molecule imaging. The current technique is an adaptation of SiMPull that provides robust quantification of the phosphorylation state of full-length membrane receptors at the single-molecule level. Imaging thousands of individual receptors in this way allows for quantifying protein phosphorylation patterns. The present protocol details the optimized SiMPull procedure, from sample preparation to imaging. Optimization of glass preparation and antibody fixation protocols further enhances data quality. The current protocol provides code for the single-molecule data analysis that calculates the fraction of receptors phosphorylated within a sample. While this work focuses on phosphorylation of the epidermal growth factor receptor (EGFR), the protocol can be generalized to other membrane receptors and cytosolic signaling molecules.

High-precision estimation of emitter positions using Bayesian grouping of localizations.

Single-molecule localization microscopy super-resolution methods rely on stochastic blinking/binding events, which often occur multiple times from each emitter over the course of data acquisition. Typically, the blinking/binding events from each emitter are treated as independent events, without an attempt to assign them to a particular emitter. Here, we describe a Bayesian method of inferring the positions of the tagged molecules by exploring the possible grouping and combination of localizations from multiple blinking/binding events. The results are position estimates of the tagged molecules that have improved localization precision and facilitate nanoscale structural insights. The Bayesian framework uses the localization precisions to learn the statistical distribution of the number of blinking/binding events per emitter and infer the number and position of emitters. We demonstrate the method on a range of synthetic data with various emitter densities, DNA origami constructs and biological structures using DNA-PAINT and dSTORM data. We show that under some experimental conditions it is possible to achieve sub-nanometer precision.

Logic-gated antibody pairs that selectively act on cells co-expressing two antigens.

The use of therapeutic monoclonal antibodies is constrained because single antigen targets often do not provide sufficient selectivity to distinguish diseased from healthy tissues. We present HexElect®, an approach to enhance the functional selectivity of therapeutic antibodies by making their activity dependent on clustering after binding to two different antigens expressed on the same target cell. lmmunoglobulin G (lgG)-mediated clustering of membrane receptors naturally occurs on cell surfaces to trigger complement- or cell-mediated effector functions or to initiate intracellular signaling. We engineer the Fc domains of two different lgG antibodies to suppress their individual homo-oligomerization while promoting their pairwise hetero-oligomerization after binding co-expressed antigens. We show that recruitment of complement component C1q to these hetero-oligomers leads to clustering-dependent activation of effector functions such as complement mediated killing of target cells or activation of cell surface receptors. HexElect allows selective antibody activity on target cells expressing unique, potentially unexplored combinations of surface antigens.

Comparing lifeact and phalloidin for super-resolution imaging of actin in fixed cells.

Visualizing actin filaments in fixed cells is of great interest for a variety of topics in cell biology such as cell division, cell movement, and cell signaling. We investigated the possibility of replacing phalloidin, the standard reagent for super-resolution imaging of F-actin in fixed cells, with the actin binding peptide 'lifeact'. We compared the labels for use in single molecule based super-resolution microscopy, where AlexaFluor 647 labeled phalloidin was used in a dSTORM modality and Atto 655 labeled lifeact was used in a single molecule imaging, reversible binding modality. We found that imaging with lifeact had a comparable resolution in reconstructed images and provided several advantages over phalloidin including lower costs, the ability to image multiple regions of interest on a coverslip without degradation, simplified sequential super-resolution imaging, and more continuous labeling of thin filaments.

Robust, fiducial-free drift correction for super-resolution imaging.

We describe a robust, fiducial-free method of drift correction for use in single molecule localization-based super-resolution methods. The method combines periodic 3D registration of the sample using brightfield images with a fast post-processing algorithm that corrects residual registration errors and drift between registration events. The method is robust to low numbers of collected localizations, requires no specialized hardware, and provides stability and drift correction for an indefinite time period.

γ9δ2T cell diversity and the receptor interface with tumor cells.

γ9δ2T cells play a major role in cancer immune surveillance, yet the clinical translation of their in vitro promise remains challenging. To address limitations of previous clinical attempts using expanded γ9δ2T cells, we explored the clonal diversity of γ9δ2T cell repertoires and characterized their target. We demonstrated that only a fraction of expanded γ9δ2T cells was active against cancer cells and that activity of the parental clone, or functional avidity of selected γ9δ2 T cell receptors (γ9δ2TCRs), was not associated with clonal frequency. Furthermore, we analyzed the target-receptor interface and provided a 2-receptor, 3-ligand model. We found that activation was initiated by binding of the γ9δ2TCR to BTN2A1 through the regions between CDR2 and CDR3 of the TCR γ chain and modulated by the affinity of the CDR3 region of the TCRδ chain, which was phosphoantigen independent (pAg independent) and did not depend on CD277. CD277 was secondary, serving as a mandatory coactivating ligand. We found that binding of CD277 to its putative ligand did not depend on the presence of γ9δ2TCR, did depend on usage of the intracellular CD277, created pAg-dependent proximity to BTN2A1, enhanced cell-cell conjugate formation, and stabilized the immunological synapse (IS). This process critically depended on the affinity of the γ9δ2TCR and required membrane flexibility of the γ9δ2TCR and CD277, facilitating their polarization and high-density recruitment during IS formation.

Bayesian Multiple Emitter Fitting using Reversible Jump Markov Chain Monte Carlo.

In single molecule localization-based super-resolution imaging, high labeling density or the desire for greater data collection speed can lead to clusters of overlapping emitter images in the raw super-resolution image data. We describe a Bayesian inference approach to multiple-emitter fitting that uses Reversible Jump Markov Chain Monte Carlo to identify and localize the emitters in dense regions of data. This formalism can take advantage of any prior information, such as emitter intensity and density. The output is both a posterior probability distribution of emitter locations that includes uncertainty in the number of emitters and the background structure, and a set of coordinates and uncertainties from the most probable model.

Mannan Molecular Substructures Control Nanoscale Glucan Exposure in Candida.

Cell wall mannans of Candida albicans mask ß-(1,3)-glucan from recognition by Dectin-1, contributing to innate immune evasion. Glucan exposures are predominantly single receptor-ligand interaction sites of nanoscale dimensions. Candida species vary in basal glucan exposure and molecular complexity of mannans. We used super-resolution fluorescence imaging and a series of protein mannosylation mutants in C. albicans and C. glabrata to investigate the role of specific N-mannan features in regulating the nanoscale geometry of glucan exposure. Decreasing acid labile mannan abundance and α-(1,6)-mannan backbone length correlated most strongly with increased density and nanoscopic size of glucan exposures in C. albicans and C. glabrata, respectively. Additionally, a C. albicans clinical isolate with high glucan exposure produced similarly perturbed N-mannan structures and elevated glucan exposure geometry. Thus, acid labile mannan structure influences the nanoscale features of glucan exposure, impacting the nature of the pathogenic surface that triggers immunoreceptor engagement, aggregation, and signaling.

Mechanism of Stx17 recruitment to autophagosomes via IRGM and mammalian Atg8 proteins.

Autophagy is a conserved eukaryotic process with metabolic, immune, and general homeostatic functions in mammalian cells. Mammalian autophagosomes fuse with lysosomes in a SNARE-driven process that includes syntaxin 17 (Stx17). How Stx17 translocates to autophagosomes is unknown. In this study, we show that the mechanism of Stx17 recruitment to autophagosomes in human cells entails the small guanosine triphosphatase IRGM. Stx17 directly interacts with IRGM, and efficient Stx17 recruitment to autophagosomes requires IRGM. Both IRGM and Stx17 directly interact with mammalian Atg8 proteins, thus being guided to autophagosomes. We also show that Stx17 is significant in defense against infectious agents and that Stx17-IRGM interaction is targeted by an HIV virulence factor Nef.

Mechanisms of inside-out signaling of the high-affinity IgG receptor FcγRI.

Fc receptors (FcRs) are an important bridge between the innate and adaptive immune system. Fc gamma receptor I (FcγRI; CD64), the high-affinity receptor for immunoglobulin G (IgG), plays roles in inflammation, autoimmune responses, and immunotherapy. Stimulation of myeloid cells with cytokines, such as tumor necrosis factor-α ( TNFα) and interferon-γ ( IFNγ), increases the binding of FcγRI to immune complexes (ICs), such as antibody-opsonized pathogens or tumor cells, through a process known as "inside-out" signaling. Using super-resolution imaging, we found that stimulation of cells with IL-3 also enhanced the clustering of FcγRI both before and after exposure to ICs. This increased clustering was dependent on an intact actin cytoskeleton. We found that chemical inhibition of the activity of the phosphatase PP1 reduced FcγRI inside-out signaling, although the phosphorylation of FcγRI itself was unaffected. Furthermore, the antibody-dependent cytotoxic activity of human neutrophils toward CD20-expressing tumor cells was increased after stimulation with TNFα and IFNγ. These results suggest that nanoscale reorganization of FcγRI, stimulated by cytokine-induced, inside-out signaling, enhances FcγRI cellular effector functions.

A computational model for regulation of nanoscale glucan exposure in Candida albicans.

Candida albicans is a virulent human opportunistic pathogen. It evades innate immune surveillance by masking an immunogenic cell wall polysaccharide, ß-glucan, from recognition by the immunoreceptor Dectin-1. Glucan unmasking by the antifungal drug caspofungin leads to changes in the nanostructure of glucan exposure accessible to Dectin-1. The physical mechanism that regulates glucan exposure is poorly understood, but it controls the nanobiology of fungal pathogen recognition. We created computational models to simulate hypothetical physical processes of unmasking glucan in a biologically realistic distribution of cell wall glucan fibrils. We tested the predicted glucan exposure nanostructural features arising from these models against experimentally measured values. A completely spatially random unmasking process, reflective of random environmental damage to the cell wall, cannot account for experimental observations of glucan unmasking. However, the introduction of partially edge biased unmasking processes, consistent with an unmasking contribution from active, local remodeling at glucan exposure sites, produces markedly more accurate predictions of experimentally observed glucan nanoexposures in untreated and caspofungin-treated yeast. These findings suggest a model of glucan unmasking wherein cell wall remodeling processes in the local nanoscale neighborhood of glucan exposure sites are an important contributor to the physical process of drug-induced glucan unmasking in C. albicans.