The synapse assembly model

Membrane signalosome: where biophysics meets systems biology

We opine on the recent advances in experiments and modeling of modular signaling complexes assembled on mammalian cell membranes (membrane signalosomes) in the context of several applications including intracellular trafficking, cell migration, and immune response. Characterizing the individual components of the membrane assemblies at the nanoscale, ranging from protein-lipid and protein-protein interactions, to membrane morphology, and the energetics of emergent assemblies at the subcellular to cellular scales pose significant challenges. Overcoming these challenges through the iterative coupling of multiscale modeling and experiment can be transformative in terms of addressing the gaps between structural biology and super-resolution microscopy, as it holds the key to the discovery of fundamental mechanisms behind the emergence of function in the membrane signalosome.

Mechanosensing in the immune response

Cells have a remarkable ability to sense and respond to the mechanical properties of their environment. Mechanosensing is essential for many phenomena, ranging from cell movements and tissue rearrangements to cell differentiation and the immune response. Cells of the immune system get activated when membrane receptors bind to cognate antigen on the surface of antigen presenting cells. Both T and B lymphocyte signaling has been shown to be responsive to physical forces and mechanical cues. Cytoskeletal forces exerted by cells likely mediate this mechanical modulation. Here, we discuss recent advances in the field of immune cell mechanobiology at the molecular and cellular scale.

Mathematical Modeling of Synaptic Patterns

During antigen recognition by T cells, a specific spatial structure is formed at the contact face to an antigen-presenting cell (APC), called an immunological synapse (IS). The IS supports bidirectional signaling and release of effector molecules and is widely studied both biologically and numerically, in order to understand the process of T cell activation and signaling. This specialized structure harbors a central area (central supramolecular activation cluster, cSMAC) populated by T cell receptor-peptide-major histocompatibility complex (TCR-pMHC ) interactions, hedged by a peripheral ring (peripheral supramolecular activation cluster, pSMAC) of integrin lymphocyte function associated-1 interactions with its immunoglobulin superfamily ligand intercellular adhesion molecule-1 (LFA-1-ICAM-1). These two regions form the "bull's eye" pattern characteristic of the mature IS.In theoretical studies, different modeling architectures, including partial differential equations (PDE) and agent-based models , have been developed with the purpose to answer mechanistic questions about the IS dynamics. In this chapter, we explain possible physiological mechanisms that lead to the formation of ISs and technical issues that may occur in the course of development of agent-based models.

Multiscale modelling in immunology: a review

One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases.

Phagocytosis of immunoglobulin-coated emulsion droplets

Phagocytosis by macrophages represents a fundamental process essential for both immunity and tissue homeostasis. The size of targets to be eliminated ranges from small particles as bacteria to large objects as cancerous or senescent cells. Most of our current quantitative knowledge on phagocytosis is based on the use of solid polymer microparticles as model targets that are well adapted to the study of phagocytosis mechanisms that do not involve any lateral mobility of the ligands, despite the relevance of this parameter in the immunological context. Herein we designed monodisperse, IgG-coated emulsion droplets that are efficiently and specifically internalized by macrophages through in-vitro FcγR-mediated phagocytosis. We show that, contrary to solid polymeric beads, droplet uptake is efficient even for low IgG densities, and is accompagnied by the clustering of the opsonins in the zone of contact with the macrophage during the adhesion step. Beyond the sole interest in the design of the material, our results suggest that lateral mobility of proteins at the interface of a target greatly enhances the phagocytic uptake.

Mesoscale computational studies of membrane bilayer remodeling by curvature-inducing proteins

Biological membranes constitute boundaries of cells and cell organelles. These membranes are soft fluid interfaces whose thermodynamic states are dictated by bending moduli, induced curvature fields, and thermal fluctuations. Recently, there has been a flood of experimental evidence highlighting active roles for these structures in many cellular processes ranging from trafficking of cargo to cell motility. It is believed that the local membrane curvature, which is continuously altered due to its interactions with myriad proteins and other macromolecules attached to its surface, holds the key to the emergent functionality in these cellular processes. Mechanisms at the atomic scale are dictated by protein-lipid interaction strength, lipid composition, lipid distribution in the vicinity of the protein, shape and amino acid composition of the protein, and its amino acid contents. The specificity of molecular interactions together with the cooperativity of multiple proteins induce and stabilize complex membrane shapes at the mesoscale. These shapes span a wide spectrum ranging from the spherical plasma membrane to the complex cisternae of the Golgi apparatus. Mapping the relation between the protein-induced deformations at the molecular scale and the resulting mesoscale morphologies is key to bridging cellular experiments across the various length scales. In this review, we focus on the theoretical and computational methods used to understand the phenomenology underlying protein-driven membrane remodeling. Interactions at the molecular scale can be computationally probed by all atom and coarse grained molecular dynamics (MD, CGMD), as well as dissipative particle dynamics (DPD) simulations, which we only describe in passing. We choose to focus on several continuum approaches extending the Canham - Helfrich elastic energy model for membranes to include the effect of curvature-inducing proteins and explore the conformational phase space of such systems. In this description, the protein is expressed in the form of a spontaneous curvature field. The approaches include field theoretical methods limited to the small deformation regime, triangulated surfaces and particle-based computational models to investigate the large-deformation regimes observed in the natural state of many biological membranes. Applications of these methods to understand the properties of biological membranes in homogeneous and inhomogeneous environments of proteins, whose underlying curvature fields are either isotropic or anisotropic, are discussed. The diversity in the curvature fields elicits a rich variety of morphological states, including tubes, discs, branched tubes, and caveola. Mapping the thermodynamic stability of these states as a function of tuning parameters such as concentration and strength of curvature induction of the proteins is discussed. The relative stabilities of these self-organized shapes are examined through free-energy calculations. The suite of methods discussed here can be tailored to applications in specific cellular settings such as endocytosis during cargo trafficking and tubulation of filopodial structures in migrating cells, which makes these methods a powerful complement to experimental studies.

Minimal mesoscale model for protein-mediated vesiculation in clathrin-dependent endocytosis

In eukaryotic cells, the internalization of extracellular cargo via the endocytic machinery is an important regulatory process required for many essential cellular functions. The role of cooperative protein-protein and protein-membrane interactions in the ubiquitous endocytic pathway in mammalian cells, namely the clathrin-dependent endocytosis, remains unresolved. We employ the Helfrich membrane Hamiltonian together with surface evolution methodology to address how the shapes and energetics of vesicular-bud formation in a planar membrane are stabilized by presence of the clathrin-coat assembly. Our results identify a unique dual role for the tubulating protein epsin: multiple epsins localized spatially and orientationally collectively play the role of a curvature inducing capsid; in addition, epsin serves the role of an adapter in binding the clathrin coat to the membrane. Our results also suggest an important role for the clathrin lattice, namely in the spatial- and orientational-templating of epsins. We suggest that there exists a critical size of the coat above which a vesicular bud with a constricted neck resembling a mature vesicle is stabilized. Based on the observed strong dependence of the vesicle diameter on the bending rigidity, we suggest that the variability in bending stiffness due to variations in membrane composition with cell type can explain the experimentally observed variability on the size of clathrin-coated vesicles, which typically range 50-100 nm. Our model also provides estimates for the number of epsins involved in stabilizing a coated vesicle, and without any direct fitting reproduces the experimentally observed shapes of vesicular intermediates as well as their probability distributions quantitatively, in wildtype as well as CLAP IgG injected neuronal cell experiments. We have presented a minimal mesoscale model which quantitatively explains several experimental observations on the process of vesicle nucleation induced by the clathrin-coated assembly prior to vesicle scission in clathrin dependent endocytosis.

Cytotoxic immunological synapses

One of the most fundamental activities of the adaptive immune system is to kill infected cells and tumor cells. Two distinct pathways mediate this process, both of which are facilitated by a cytotoxic immunological synapse. While traditionally thought of as innate immune cells, natural killer (NK) cells are now appreciated to have the capacity for long-term adaptation to chemical and viral insults. These cells integrate multiple positive and negative signals through NK cell cytotoxic or inhibitory synapses. The traditional CD8(+)alphabeta T-cell receptor-positive cells are among the best models for the concept of an immunological synapse, in which vectoral signaling is linked to directed secretion in a stable interface to induce apoptotic cell death in an infected cell. Large-scale molecular organization in synapses generated a number of hypotheses. Studies in the past 5 years have started to provide clear answers regarding the validity of these models. In vivo imaging approaches have provided some hints as to the physiologic relevance of these processes with great promise for the future. This review provides an overview of work on cytotoxic immunological synapses and suggests pathways forward in applying this information to the development of therapeutic agents.

Calculation of free energies in fluid membranes subject to heterogeneous curvature fields

We present a computational methodology for incorporating thermal effects and calculating relative free energies for elastic fluid membranes subject to spatially dependent intrinsic curvature fields using the method of thermodynamic integration. Based on a simple model for the intrinsic curvature imposed only in a localized region of the membrane, we employ thermodynamic integration to calculate the free-energy change as a function of increasing strength of the intrinsic curvature field and a thermodynamic cycle to compute free-energy changes for different sizes of the localized region. By explicitly computing the free-energy changes and by quantifying the loss of entropy accompanied with increasing membrane deformation, we show that the membrane stiffness increases with increasing intrinsic field, thereby, renormalizing the membrane bending rigidity. The second main conclusion of this work is that the entropy of the membrane decreases with increasing size of the localized region subject to the curvature field. Our results help to quantify the free-energy change when a planar membrane deforms under the influence of curvature-inducing proteins at a finite temperature.

Versatile analysis of single-molecule tracking data by comprehensive testing against Monte Carlo simulations

We propose here an approach for the analysis of single-molecule trajectories which is based on a comprehensive comparison of an experimental data set with multiple Monte Carlo simulations of the diffusion process. It allows quantitative data analysis, particularly whenever analytical treatment of a model is infeasible. Simulations are performed on a discrete parameter space and compared with the experimental results by a nonparametric statistical test. The method provides a matrix of p-values that assess the probability for having observed the experimental data at each setting of the model parameters. We show the testing approach for three typical situations observed in the cellular plasma membrane: i), free Brownian motion of the tracer, ii), hop diffusion of the tracer in a periodic meshwork of squares, and iii), transient binding of the tracer to slowly diffusing structures. By plotting the p-value as a function of the model parameters, one can easily identify the most consistent parameter settings but also recover mutual dependencies and ambiguities which are difficult to determine by standard fitting routines. Finally, we used the test to reanalyze previous data obtained on the diffusion of the glycosylphosphatidylinositol-protein CD59 in the plasma membrane of the human T24 cell line.

Landscape of finite-temperature equilibrium behaviour of curvature-inducing proteins on a bilayer membrane explored using a linearized elastic free energy model

Using a recently developed multiscale simulation methodology, we describe the equilibrium behaviour of bilayer membranes under the influence of curvature-inducing proteins using a linearized elastic free energy model. In particular, we describe how the cooperativity associated with a multitude of protein-membrane interactions and protein diffusion on a membrane-mediated energy landscape elicits emergent behaviour in the membrane phase. Based on our model simulations, we predict that, depending on the density of membrane-bound proteins and the degree to which a single protein molecule can induce intrinsic mean curvature in the membrane, a range of membrane phase behaviour can be observed including two different modes of vesicle-bud nucleation and repressed membrane undulations. A state diagram as a function of experimentally tunable parameters to classify the underlying states is proposed.

A hybrid deterministic-stochastic algorithm for modeling cell signaling dynamics in spatially inhomogeneous environments and under the influence of external fields

Cell signaling dynamics mediate myriad processes in biology. It has become increasingly clear that inter- and intracellular signaling reactions often occur in a spatially inhomogeneous environment and that it is important to account for stochastic fluctuations of certain species involved in signaling reactions. The importance of these effects enhances the difficulty of gleaning mechanistic information from observations of a few experimental reporters and highlights the significance of synergistic experimental and computational studies. When both stochastic fluctuations and spatial inhomogeneity must be included in a model simultaneously, however, the resulting computational demands quickly become overwhelming. In many situations the failure of standard coarse-graining methods (i.e., ignoring spatial variation or stochastic fluctuations) when applied to all components of a complex system does not exclude the possibility of successfully applying such coarse-graining to some components of the system. Following this approach alleviates computational cost but requires "hybrid" algorithms where some variables are treated at a coarse-grained level while others are not. We present an efficient algorithm for simulation of stochastic, spatially inhomogeneous reaction-diffusion kinetics coupled to coarse-grained fields described by (stochastic or deterministic) partial differential equations (PDEs). The PDEs could represent mean-field descriptions of reactive species present in large copy numbers or evolution of hydrodynamic variables that influence signaling (e.g., membrane shape or cytoskeletal motion). We discuss the approximations made to derive our algorithm and test its efficacy by applying it to problems that include many features typical of realistic cell signaling processes.

Curvature and spatial organization in biological membranes

Cellular membranes bend and curve into a multitude of shapes as they perform various functions. These deformations make use of the remarkable material properties of biological membranes inherent in their nature as two-dimensional fluids. The curvature of membranes is controlled by the constituent proteins and lipids, but conversely, curvature itself provides mechanisms for organizing mobile membrane molecules. In this article we survey recent experiments that have uncovered intriguing connections between mechanics and biochemistry at membranes, focusing on the influence of molecular shape on curvature, links between phase separation and curvature, and membrane bending at inter-cellular contacts. We describe the concepts that emerge from these studies, especially the existence of long-range, curvature-mediated mechanisms for spatial organization in membranes, and highlight open areas for future research.

Synaptic proteins as multi-sensor devices of neurotransmission

Neuronal communication is tightly regulated in time and space. Following neuronal activation, an electrical signal triggers neurotransmitter (NT) release at the active zone. The process starts by the signal reaching the synapse followed by a fusion of the synaptic vesicle (SV) and diffusion of the released NT in the synaptic cleft. The NT then binds to the appropriate receptor and induces a membrane potential change at the target cell membrane. The entire process is controlled by a fairly small set of synaptic proteins, collectively called SYCONs. The biochemical features of SYCONs underlie the properties of NT release. SYCONs are characterized by their ability to detect and respond to changes in environmental signals. For example, consider synaptotagmin I (Syt1), a prototype of a protein family with over 20 gene and variants in mammals. Syt1 is a specific example of a multi-sensor device with a large repertoire of discrete states. Several of these states are stimulated by a local concentration of signaling molecules such as Ca2+. The ability of this protein to sense signaling molecules and to adopt multiple biochemical states is shared by other SYCONs such as the synapsins (Syns). Specific biochemical states of Syns determine the accessibility of SV for NT release. Each of these states is defined by a specific alternative spliced variant with a unique profile of phosphorylation modified sites. The plasticity of the synapse is a direct reflection of SYCON's multiple biochemical states. State transitions occurs in a wide range of time scales, and therefore these molecules need to cope with events that last milliseconds (i.e., exocytosis in fast responding synapses) and with events that can carry on for many minutes (i.e., organization of SV pools). We suggest that SYCONs are optimized throughout evolution as multi-sensor devices. A full repertoire of the switches leading to alternation of protein states and a detailed characterization of protein-protein network within the synapse is critical for the development of a dynamic model of synaptic transmission.

B cell ligand discrimination through a spreading and contraction response

B cells recognize foreign antigens by virtue of cell surface immunoglobulin receptors and are most effectively activated by membrane-bound ligands. Here, we show that in the early stages of this process, B cells exhibit a two-phase response in which they first spread over the antigen-bearing membrane and then contract, thereby collecting bound antigen into a central aggregate. The extent of this response, which is both signaling- and actin-dependent, determines the quantity of antigen accumulated and hence the degree of B cell activation. Brownian dynamic simulations reproduce essential features of the antigen collection process and suggest a possible basis for affinity discrimination. We propose that dynamic spreading is an important step of the immune response.

The secrets of a functional synapse--from a computational and experimental viewpoint

Background

Neuronal communication is tightly regulated in time and in space. The neuronal transmission takes place in the nerve terminal, at a specialized structure called the synapse. Following neuronal activation, an electrical signal triggers neurotransmitter (NT) release at the active zone. The process starts by the signal reaching the synapse followed by a fusion of the synaptic vesicle and diffusion of the released NT in the synaptic cleft; the NT then binds to the appropriate receptor, and as a result, a potential change at the target cell membrane is induced. The entire process lasts for only a fraction of a millisecond. An essential property of the synapse is its capacity to undergo biochemical and morphological changes, a phenomenon that is referred to as synaptic plasticity.

Results

In this survey, we consider the mammalian brain synapse as our model. We take a cell biological and a molecular perspective to present fundamental properties of the synapse:(i) the accurate and efficient delivery of organelles and material to and from the synapse; (ii) the coordination of gene expression that underlies a particular NT phenotype; (iii) the induction of local protein expression in a subset of stimulated synapses. We describe the computational facet and the formulation of the problem for each of these topics.

Conclusion

Predicting the behavior of a synapse under changing conditions must incorporate genomics and proteomics information with new approaches in computational biology.

'KMC-TDGL'-a coarse-grained methodology for simulating interfacial dynamics in complex fluids: application to protein-mediated membrane processes

In this article, we describe a new multiscale simulation algorithm (which we term the 'KMC-TDGL' method) applicable for the description of equilibrium and dynamic processes associated with a particular class of complex fluids with nanoscale inclusions, namely, biological membranes mediated by membrane-associating and membrane-bound proteins. We adopt a novel strategy of integrating two different phenomenological approaches, namely, a field theoretic (continuum) description for the membrane dynamics given by the time-dependent Ginzburg-Landau equation and a random walk on a discretized lattice description for protein diffusion dynamics. We illustrate that this integrated approach results in a unified description of protein-mediated membrane dynamics.

A Theoretical Framework for Quantitative Analysis of the Molecular Basis of Costimulation

We present a theoretical framework for simulating the synaptic accumulation of the costimulatory molecules CD28, CTLA-4, B7-1, and B7-2, based on a system of mean-field, ordinary differential equations, and rigorous biophysical and expression data. The simulations show that binding affinity, stoichiometric properties, expression levels, and, in particular, competition effects all profoundly influence complex formation at cellular interfaces. B7-2 engages 33-fold more CD28 than CTLA-4 at the synapse in contrast to B7-1, which ligates approximately 7-fold more CTLA-4 than CD28. Although B7-1 completely dominates interactions with CTLA-4, forming linear arrays of 7-18 receptor-ligand pairs, CTLA-4 is fully engaged by B7-2 when B7-1 is absent. Additional simulations reveal the sensitivity of CD28 interactions to modeled transport processes. The results support the concept that B7-2 and B7-1 are the dominant ligands of CD28 and CTLA-4, respectively, and indicate that the inability of B7-2 to recruit CTLA-4 to the synapse cannot be due to the differential binding properties of B7-1 and B7-2 only. We discuss the apparent redundancy of B7-1 in the context of a potentially dynamic synaptic microenvironment, and in light of functions other than the direct enhancement of T cell inhibition by CTLA-4.

Molecular Organization and Signal Transduction at Intermembrane Junctions

Surfaces create an environment in which multiple forces conspire together to yield a wealth of complex chemical processes. This is especially true of cell membranes, whose fluidity and flexibility enables responsive feedback with surface chemical interactions in ways not generally seen with inorganic materials. Spatial pattern formation of cell-surface proteins at intermembrane junctions provides many beautiful examples of these phenomena, and is also emerging as a functional aspect of intercellular signaling. Correspondingly, the study of interactions of cell-membrane surfaces is attracting significant attention from cell biologists and physical chemists alike. This convergence is fueled be recent, exquisite observations of protein pattern formation events within living immunological synapses along with parallel advances in membrane reconstitution, manipulation, and imaging technologies.

Nanomechanics of adhesion proteins

Recent advances in molecular force measurements have resulted in the quantification of the nanomechanical properties of single molecular bonds, and elucidated novel relationships between molecular architecture and biomolecular adhesion. The measured forces to rupture single intermolecular bonds revealed novel and unexpected ways that proteins respond to mechanical force. Measurement of the magnitude of interprotein forces and the distances over which they act further determined how protein architecture may contribute to both the stability and structural organization of adhesive junctions.

Equilibrium thermodynamics of cell-cell adhesion mediated by multiple ligand-receptor pairs

In many situations, cell-cell adhesion is mediated by multiple ligand-receptor pairs. For example, the interaction between T cells and antigen-presenting cells of the immune system is mediated not only by T cell receptors and their ligands (peptide-major histocompatibility complex) but also by binding of intracellular adhesion molecules. Interestingly, these binding pairs have different resting lengths. Fluorescent labeling reveals segregation of the longer adhesion molecules from the shorter T cell receptors in this case. Here, we explore the thermal equilibrium of a general cell-cell interaction mediated by two ligand-receptor pairs to examine competition between the elasticity of the cell wall, nonspecific intercellular repulsion, and bond formation, leading to segregation of bonds of different lengths at equilibrium. We make detailed predictions concerning the relationship between physical properties of the membrane and ligand-receptor pairs and equilibrium pattern formation, and suggest experiments to refine our understanding of the system. We demonstrate our model by application to the T cell/antigen-presenting-cell system and outline applications to natural killer cell adhesion.

LFA-1/ICAM-1 Interaction Lowers the Threshold of B Cell Activation by Facilitating B Cell Adhesion and Synapse Formation

The integrin LFA-1 and its ligand ICAM-1 mediate B cell adhesion, but their role in membrane-bound antigen recognition is still unknown. Here, using planar lipid bilayers and cells expressing ICAM-1 fused to green fluorescence protein, we found that the engagement of B cell receptor (BCR) promotes B cell adhesion by an LFA-1-mediated mechanism. LFA-1 is recruited to form a mature B cell synapse segregating into a ring around the BCR. This distribution is maintained over a wide range of BCR/antigen affinities (10(6) M(-1) to 10(11) M(-1)). Furthermore, the LFA-1 binding to ICAM-1 reduces the level of antigen required to form the synapse and trigger a B cell. Thus, LFA-1/ICAM-1 interaction lowers the threshold for B cell activation by promoting B cell adhesion and synapse formation.

The ABCs of artificial antigen presentation

Artificial antigen presentation aims to accelerate the establishment of therapeutic cellular immunity. Artificial antigen-presenting cells (AAPCs) and their cell-free substitutes are designed to stimulate the expansion and acquisition of optimal therapeutic features of T cells before therapeutic infusion, without the need for autologous antigen-presenting cells. Compelling recent advances include fibroblast AAPCs that process antigens, magnetic beads that are antigen specific, novel T-cell costimulatory combinations, the augmentation of therapeutic potency of adoptively transferred T lymphocytes by interleukin-15, and the safe use of dendritic cell-derived exosomes pulsed with tumor antigen. Whereas the safety and potency of the various systems warrant further preclinical and clinical studies, these emerging technologies are poised to have a major impact on adoptive T-cell therapy and the investigation of T cell-mediated immunity.

ERM proteins regulate cytoskeleton relaxation promoting T cell–APC conjugation

During activation, T cells associate with antigen-presenting cells, a dynamic process that involves the formation of a broad area of intimate membrane contact known as the immunological synapse. The molecular intermediates that link initial antigen recognition to the cytoskeletal changes involved in this phenomenon have not yet been defined. Here we demonstrate that ezrin-radixin-moesin proteins are rapidly inactivated after antigen recognition through a Vav1-Rac1 pathway. The resulting disanchoring of the cortical actin cytoskeleton from the plasma membrane decreased cellular rigidity, leading to more efficient T cell-antigen-presenting cell conjugate formation. These findings identify an antigen-dependent molecular pathway that favors immunological synapse formation and the subsequent development of an effective immune response.

Quantitative analysis of the contribution of TCR/pepMHC affinity and CD8 to T cell activation

The relative roles of CD8, TCR:pepMHC affinity, and TCR:pepMHC dissociation rate in T cell activation have remained controversial. To determine the relationships among these factors, we used T cells transfected with normal and in vitro engineered alphabeta TCRs, in the presence or absence of CD8. The TCRs exhibited a wide range of affinities (K(D) values of 80 microM to 5 nM). T cells with the highest affinity TCRs were efficiently stimulated by peptide, with or without CD8. In contrast, CD8 was required for T cells that expressed TCRs with affinities typical of syngeneic reactions (K(D) values above approximately 3 microM). The results suggest that virtually all normal syngeneic interactions require CD8, which enhances peptide sensitivity by one million-fold or more.