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.

Using hierarchical clustering and dendrograms to quantify the clustering of membrane proteins.

Cell biologists have developed methods to label membrane proteins with gold nanoparticles and then extract spatial point patterns of the gold particles from transmission electron microscopy images using image processing software. Previously, the resulting patterns were analyzed using the Hopkins statistic, which distinguishes nonclustered from modestly and highly clustered distributions, but is not designed to quantify the number or sizes of the clusters. Clusters were defined by the partitional clustering approach which required the choice of a distance. Two points from a pattern were put in the same cluster if they were closer than this distance. In this study, we present a new methodology based on hierarchical clustering to quantify clustering. An intrinsic distance is computed, which is the distance that produces the maximum number of clusters in the biological data, eliminating the need to choose a distance. To quantify the extent of clustering, we compare the clustering distance between the experimental data being analyzed with that from simulated random data. Results are then expressed as a dimensionless number, the clustering ratio that facilitates the comparison of clustering between experiments. Replacing the chosen cluster distance by the intrinsic clustering distance emphasizes densely packed clusters that are likely more important to downstream signaling events.We test our new clustering analysis approach against electron microscopy images from an experiment in which mast cells were exposed for 1 or 2 minutes to increasing concentrations of antigen that crosslink IgE bound to its high affinity receptor, FcϵRI, then fixed and the FcϵRI ß subunit labeled with 5 nm gold particles. The clustering ratio analysis confirms the increase in clustering with increasing antigen dose predicted from visual analysis and from the Hopkins statistic. Access to a robust and sensitive tool to both observe and quantify clustering is a key step toward understanding the detailed fine scale structure of the membrane, and ultimately to determining the role of spatial organization in the regulation of transmembrane signaling.

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.

Activated N-formyl peptide receptor and high-affinity IgE receptor occupy common domains for signaling and internalization.

Immune cells display multiple cell surface receptors that integrate signals for survival, proliferation, migration, and degranulation. Here, immunogold labeling is used to map the plasma membrane distributions of two separate receptors, the N-formyl peptide receptor (FPR) and the high-affinity IgE receptor (FepsilonRI). We show that the FPR forms signaling clusters in response to monovalent ligand. These domains recruit Gi, followed by the negative regulatory molecule arrestin2. There are low levels of colocalization of FPR with FcepsilonRI in unstimulated cells, shown by computer simulation to be a consequence of receptor density. Remarkably, there is a large increase in receptor coclustering when cells are simultaneously treated with N-formyl-methionyl-leucyl-phenylalanine and IgE plus polyvalent antigen. The proximity of two active receptors may promote localized cross-talk, leading to enhanced inositol-(3,4,5)-trisphosphate production and secretion. Some cointernalization and trafficking of the two receptors can be detected by live cell imaging, but the bulk of FPR and FcepsilonRI segregates over time. This segregation is associated with more efficient internalization of cross-linked FcepsilonRI than of arrestin-desensitized FPR. The observation of receptors in lightly coated membrane invaginations suggests that, despite the lack of caveolin, hematopoietic cells harbor caveolae-like structures that are candidates for nonclathrin-mediated endocytosis.

Markers for detergent-resistant lipid rafts occupy distinct and dynamic domains in native membranes.

Lipid rafts isolated by detergent extraction and sucrose gradient fractionation from mast cells are enriched for the glycosylphosphatidylinositol-linked protein Thy-1, the ganglioside GM1, palmitoylated LAT, and cross-linked IgE receptors, FcepsilonRI. This study addresses the relationship of fractionation data to the organization of raft markers in native membranes. Immunogold labeling and electron microscopy shows there is little or no colocalization of the raft markers Thy-1, GM1, and LAT with each other or with FcepsilonRI on native membrane sheets prepared from unstimulated cells. External cross-linking of Thy-1 promotes coclustering of Thy-1 with LAT, but not with GM1. Thy-1 and LAT clusters occur on membrane regions without distinctive features. In contrast, external cross-linking of FcepsilonRI and GM1 causes their redistribution to electron-dense membrane patches independently of each other and of Thy-1. The distinctive patches that accumulate cross-linked FcepsilonRI and GM1 also accumulate osmium, a stain for unsaturated lipids, and are sites for coated vesicle budding. Electron microscopy reveals a more complex and dynamic topographical organization of membrane microdomains than is predicted by biochemical analysis of detergent-resistant membranes.

Characterizing the topography of membrane receptors and signaling molecules from spatial patterns obtained using nanometer-scale electron-dense probes and electron microscopy.

The flow of information through a cell requires the constant remodeling of cell signaling networks. Thus, spatially and temporally resolved microscopy of signaling components is needed to understand the behavior of normal cells as well as to uncover abnormal behavior leading to human disease. Nanoprobe labeling and transmission electron microscopy of cytoplasmic face-up sheets of cell membrane have been developed as a high-resolution approach to map the interactions of proteins and lipid during cell signaling. Membrane sheets are labeled with 3-15 nm electron-dense probes for receptors, signaling proteins and lipids and micrographs record the distributions of the probes relative to each other and to surface features. Here, we establish computational methods to extract spatial coordinates of probes from micrographs, to analyze and statistically validate the clustering and co-clustering of these probes and to integrate results between experiments in order to establish the relative spatial distributions of single and multiple probes. Our analyses, and the resulting programs for automating data collection and for carrying out statistical and clustering analyses provide toolboxes specialized for the spatiotemporal analysis and modeling of signal transduction pathways.

Membrane receptor mapping: the membrane topography of Fc(epsilon)RI signaling.

Ligand binding to membrane receptors initiates cascades of biochemical events leading to physiological responses. Hundreds of proteins and lipids are implicated in signaling networks and programs in genomics and proteomics are continuously adding new components to the signaling "parts lists". Here, we generate high resolution maps of signaling networks using cytoplasmic face-up membrane sheets that can be labeled with immunogold probes (3-10 nm) and imaged in the transmission electron microscope. Our model system is the mast cell and we focus on mapping the topography of the high affinity IgE receptor, Fc(epsilon)RI, its associated tyrosine kinases, Lyn and Syk, and the signaling proteins that propagate signals from these kinases. Crosslinked receptors and their signaling partners segregate during signaling to multiple, dynamic membrane domains, including a transient Fc(epsilon)RI-Lyn domain and at least two other distinct domains, one characterized by the presence of receptor, Syk and multiple signaling proteins, but not Lyn (primary signaling domains), and one characterized by the presence of LAT and PLCgamma1 but not receptor (secondary signaling domains). PI 3-kinase associates with both primary and secondary signaling domains and may help to recruit specific signaling proteins through the local remodeling of inositol phospholipids. The lipid raft markers, GM1 and Thy-1, fail to localize in native membrane sheets either with each other or with signaling domains. We introduce new probes to localize multiple signaling molecules on the same membrane sheet and new computational tools to capture and analyze their topographical relationships. In the future, we expect that high resolution maps of signaling networks will be integrated with chemical kinetic analyses, with cell fractionation data and with a range of real-time fluorescence measurements, into mathematical models with power to predict mechanisms that regulate the efficiency, specificity, amplitude and duration of signaling pathways.

Markov random field modeling of the spatial distribution of proteins on cell membranes.

Cell membranes display a range of receptors that bind ligands and activate signaling pathways. Signaling is characterized by dramatic changes in membrane molecular topography, including the co-clustering of receptors with signaling molecules and the segregation of other signaling molecules away from receptors. Electron microscopy of immunogold-labeled membranes is a critical technique to generate topographical information at the 5-10 nm resolution needed to understand how signaling complexes assemble and function. However, due to experimental limitations, only two molecular species can usually be labeled at a time. A formidable challenge is to integrate experimental data across multiple experiments where there are from 10 to 100 different proteins and lipids of interest and only the positions of two species can be observed simultaneously. As a solution, we propose the use of Markov random field (MRF) modeling to reconstruct the distribution of multiple cell membrane constituents from pair-wise data sets. MRFs are a powerful mathematical formalism for modeling correlations between states associated with neighboring sites in spatial lattices. The presence or absence of a protein of a specific type at a point on the cell membrane is a state. Since only two protein types can be observed, i.e., those bound to particles, and the rest cannot be observed, the problem is one of deducing the conditional distribution of a MRF with unobservable (hidden) states. Here, we develop a multiscale MRF model and use mathematical programming techniques to infer the conditional distribution of a MRF for proteins of three types from observations showing the spatial relationships between only two types. Application to synthesized data shows that the spatial distributions of three proteins can be reliably estimated. Application to experimental data provides the first maps of the spatial relationship between groups of three different signaling molecules. The work is an important step toward a more complete understanding of membrane spatial organization and dynamics during signaling.

Mapping ErbB receptors on breast cancer cell membranes during signal transduction.

Distributions of ErbB receptors on membranes of SKBR3 breast cancer cells were mapped by immunoelectron microscopy. The most abundant receptor, ErbB2, is phosphorylated, clustered and active. Kinase inhibitors ablate ErbB2 phosphorylation without dispersing clusters. Modest co-clustering of ErbB2 and EGFR, even after EGF treatment, suggests that both are predominantly involved in homointeractions. Heregulin leads to dramatic clusters of ErbB3 that contain some ErbB2 and EGFR and abundant PI 3-kinase. Other docking proteins, such as Shc and STAT5, respond differently to receptor activation. Levels of Shc at the membrane increase two- to five-fold with EGF, whereas pre-associated STAT5 becomes strongly phosphorylated. These data suggest that the distinct topography of receptors and their docking partners modulates signaling activities.