Signal Amplification in Highly Ordered Networks Is Driven by Geometry

Here, we hypothesize that, in biological systems such as cell surface receptors that relay external signals, clustering leads to substantial improvements in signaling efficiency. Representing cooperative signaling networks as planar graphs and applying Euler’s polyhedron formula, we can show that clustering may result in an up to a 200% boost in signaling amplitude dictated solely by the size and geometry of the network. This is a fundamental relationship that applies to all clustered systems regardless of its components. Nature has figured out a way to maximize the signaling amplitude in receptors that relay weak external signals. In addition, in cell-to-cell interactions, clustering both receptors and ligands may result in maximum efficiency and synchronization. The importance of clustering geometry in signaling efficiency goes beyond biological systems and can inform the design of amplifiers in nonbiological systems.

Probing the effect of clustering on EphA2 receptor signaling efficiency by subcellular control of ligand-receptor mobility

Clustering of ligand:receptor complexes on the cell membrane is widely presumed to have functional consequences for subsequent signal transduction. However, it is experimentally challenging to selectively manipulate receptor clustering without altering other biochemical aspects of the cellular system. Here, we develop a microfabrication strategy to produce substrates displaying mobile and immobile ligands that are separated by roughly 1 µm, and thus experience an identical cytoplasmic signaling state, enabling precision comparison of downstream signaling reactions. Applying this approach to characterize the ephrinA1:EphA2 signaling system reveals that EphA2 clustering enhances both receptor phosphorylation and downstream signaling activity. Single-molecule imaging clearly resolves increased molecular binding dwell times at EphA2 clusters for both Grb2:SOS and NCK:N-WASP signaling modules. This type of intracellular comparison enables a substantially higher degree of quantitative analysis than is possible when comparisons must be made between different cells and essentially eliminates the effects of cellular response to ligand manipulation.

Probe the effect of clustering on EphA2 receptor signaling efficiency by subcellular control of ligand-receptor mobility

Clustering of ligand:receptor complexes on the cell membrane is widely presumed to have functional consequences for subsequent signal transduction. However, it is experimentally challenging to selectively manipulate receptor clustering without altering other biochemical aspects of the cellular system. Here, we develop a microfabrication strategy to produce substrates displaying mobile and immobile ligands that are separated by roughly one micron and thus experience an identical cytoplasmic signaling state, enabling precision comparison of downstream signaling reactions. Applying this approach to characterize the ephrinA1:EphA2 signaling system reveals that EphA2 clustering enhances receptor phosphorylation. Single molecule imaging clearly resolves increased molecular binding dwell time at EphA2 clusters for both Grb2:SOS and NCK:NWASP signaling modules. This type of intracellular comparison enables a substantially higher degree of quantitative analysis than is possible when comparisons must be made between different cells and essentially eliminates the effects of cellular response to ligand manipulation.

A mouse model of human TLR4 D299G/T399I SNPs reveals mechanisms of altered LPS and pathogen responses

Two cosegregating single-nucleotide polymorphisms (SNPs) in human TLR4, an A896G transition at SNP rs4986790 (D299G) and a C1196T transition at SNP rs4986791 (T399I), have been associated with LPS hyporesponsiveness and differential susceptibility to many infectious or inflammatory diseases. However, many studies failed to confirm these associations, and transfection experiments resulted in conflicting conclusions about the impact of these SNPs on TLR4 signaling. Using advanced protein modeling from crystallographic data of human and murine TLR4, we identified homologous substitutions of these SNPs in murine Tlr4, engineered a knock-in strain expressing the D298G and N397I TLR4 SNPs homozygously, and characterized in vivo and in vitro responses to TLR4 ligands and infections in which TLR4 is implicated. Our data provide new insights into cellular and molecular mechanisms by which these SNPs decrease the TLR4 signaling efficiency and offer an experimental approach to confirm or refute human data possibly confounded by variables unrelated to the direct effects of the SNPs on TLR4 functionality.

Nanoscale Organization of FasL on DNA Origami as a Versatile Platform to Tune Apoptosis Signaling in Cells

Nanoscale probes with fine-tunable properties are of key interest in cell biology and nanomedicine to elucidate and eventually control signaling processes in cells. A critical, still challenging issue is to conjugate these probes with molecules in a number- and spatially-controlled manner. Here, DNA origami-based nanoagents as nanometer precise scaffolds presenting Fas ligand (FasL) in well-defined arrangements to cells are reported. These nanoagents activate receptor molecules in the plasma membrane initiating apoptosis signaling in cells. Signaling for apoptosis depends sensitively on FasL geometry: fastest time-to-death kinetics are obtained for FasL nanoagents representing predicted structure models of hexagonal receptor ordering with 10 nm inter-molecular spacing. Slower kinetics are observed for one to two FasL on DNA origami or FasL coupled with higher flexibility. Nanoagents with FasL arranged in hexagons with small (5 nm) and large (30 nm) spacing impede signal transduction. Moreover, for predicted hexagonal FasL nanoagents, signaling efficiency is faster and 100× higher compared to naturally occurring soluble FasL. Incubation of the FasL-origami nanoagent in solution exhibited an EC50 value of only 90 pM. These studies present DNA origami as versatile signaling platforms to probe the significance of molecular number and nanoscale ordering for signal initiation in cells.

Combinatorial diversity of Syk recruitment driven by its multivalent engagement with FcεRIγ

Syk/Zap70 family kinases are essential for signaling via multichain immune-recognition receptors such as tetrameric (αβγ2) FcεRI. Syk activation is generally attributed to cis binding of its tandem SH2 domains to dual phosphotyrosines within FcεRIγ-ITAMs (immunoreceptor tyrosine-based activation motifs). However, the mechanistic details of Syk docking on γ homodimers are unresolved. Here, we estimate that multivalent interactions for WT Syk improve cis-oriented binding by three orders of magnitude. We applied molecular dynamics (MD), hybrid MD/worm-like chain polymer modeling, and live cell imaging to evaluate relative binding and signaling output for all possible cis and trans Syk–FcεRIγ configurations. Syk binding is likely modulated during signaling by autophosphorylation on Y130 in interdomain A, since a Y130E phosphomimetic form of Syk is predicted to lead to reduced helicity of interdomain A and alter Syk’s bias for cis binding. Experiments in reconstituted γ-KO cells, whose γ subunits are linked by disulfide bonds, as well as in cells expressing monomeric ITAM or hemITAM γ-chimeras, support model predictions that short distances between γ ITAM pairs are required for trans docking. We propose that the full range of docking configurations improves signaling efficiency by expanding the combinatorial possibilities for Syk recruitment, particularly under conditions of incomplete ITAM phosphorylation.

Information Thermodynamics for Time Series of Signal-Response Models

The entropy production in stochastic dynamical systems is linked to the structure of their causal representation in terms of Bayesian networks. Such a connection was formalized for bipartite (or multipartite) systems with an integral fluctuation theorem in [Phys. Rev. Lett. 111, 180603 (2013)]. Here we introduce the information thermodynamics for time series, that are non-bipartite in general, and we show that the link between irreversibility and information can only result from an incomplete causal representation. In particular, we consider a backward transfer entropy lower bound to the conditional time series irreversibility that is induced by the absence of feedback in signal-response models. We study such a relation in a linear signal-response model providing analytical solutions, and in a nonlinear biological model of receptor-ligand systems where the time series irreversibility measures the signaling efficiency.