DNA origami patterning of synthetic T cell receptors reveals spatial control of the sensitivity and kinetics of signal activation.

Receptor clustering plays a key role in triggering cellular activation, but the relationship between the spatial configuration of clusters and the elicitation of downstream intracellular signals remains poorly understood. We developed a DNA-origami-based system that is easily adaptable to other cellular systems and enables rich interrogation of responses to a variety of spatially defined inputs. Using a chimeric antigen receptor (CAR) T cell model system with relevance to cancer therapy, we studied signaling dynamics at single-cell resolution. We found that the spatial arrangement of receptors determines the ligand density threshold for triggering and encodes the temporal kinetics of signaling activities. We also showed that signaling sensitivity of a small cluster of high-affinity ligands is enhanced when surrounded by nonstimulating low-affinity ligands. Our results suggest that cells measure spatial arrangements of ligands, translate that information into distinct signaling dynamics, and provide insights into engineering immunotherapies.

Ensemble force changes that result from human cardiac myosin mutations and a small-molecule effector.

Cardiomyopathies due to mutations in human ß-cardiac myosin are a significant cause of heart failure, sudden death, and arrhythmia. To understand the underlying molecular basis of changes in the contractile system's force production due to such mutations and search for potential drugs that restore force generation, an in vitro assay is necessary to evaluate cardiac myosin's ensemble force using purified proteins. Here, we characterize the ensemble force of human α- and ß-cardiac myosin isoforms and those of ß-cardiac myosins carrying left ventricular non-compaction (M531R) and dilated cardiomyopathy (S532P) mutations using a utrophin-based loaded in vitro motility assay and new filament-tracking software. Our results show that human α- and ß-cardiac myosin, as well as the mutants, show opposite mechanical and enzymatic phenotypes with respect to each other. We also show that omecamtiv mecarbil, a previously discovered cardiac-specific myosin activator, increases ß-cardiac myosin force generation.

Direct observation of parallel folding pathways revealed using a symmetric repeat protein system.

Although progress has been made to determine the native fold of a polypeptide from its primary structure, the diversity of pathways that connect the unfolded and folded states has not been adequately explored. Theoretical and computational studies predict that proteins fold through parallel pathways on funneled energy landscapes, although experimental detection of pathway diversity has been challenging. Here, we exploit the high translational symmetry and the direct length variation afforded by linear repeat proteins to directly detect folding through parallel pathways. By comparing folding rates of consensus ankyrin repeat proteins (CARPs), we find a clear increase in folding rates with increasing size and repeat number, although the size of the transition states (estimated from denaturant sensitivity) remains unchanged. The increase in folding rate with chain length, as opposed to a decrease expected from typical models for globular proteins, is a clear demonstration of parallel pathways. This conclusion is not dependent on extensive curve-fitting or structural perturbation of protein structure. By globally fitting a simple parallel-Ising pathway model, we have directly measured nucleation and propagation rates in protein folding, and have quantified the fluxes along each path, providing a detailed energy landscape for folding. This finding of parallel pathways differs from results from kinetic studies of repeat-proteins composed of sequence-variable repeats, where modest repeat-to-repeat energy variation coalesces folding into a single, dominant channel. Thus, for globular proteins, which have much higher variation in local structure and topology, parallel pathways are expected to be the exception rather than the rule.

Analysis of repeat-protein folding using nearest-neighbor statistical mechanical models.

The linear "Ising" model, which has been around for nearly a century, treats the behavior of linear arrays of repetitive, interacting subunits. Linear "repeat-proteins" have only been described in the last decade or so, and their folding energies have only been characterized very recently. Owing to their repetitive structures, linear repeat-proteins are particularly well suited for analysis by the nearest-neighbor Ising formalism. After briefly describing the historical origins and applications of the Ising model to biopolymers, and introducing repeat protein structure, this chapter will focus on the application of the linear Ising model to repeat proteins. When applied to homopolymers, the model can be represented and applied in a fairly simplified form. When applied to heteropolymers, where differences in energies among individual subunits (i.e. repeats) must be included, some (but not all) of this simplicity is lost. Derivations of the linear Ising model for both homopolymer and heteropolymer repeat-proteins will be presented. With the increased complexity required for analysis of heteropolymeric repeat proteins, the ability to resolve different energy terms from experimental data can be compromised. Thus, a simple matrix approach will be developed to help inform on the degree to which different thermodynamic parameters can be extracted from a particular set of unfolding curves. Finally, we will describe the application of these models to analyze repeat-protein folding equilibria, focusing on simplified repeat proteins based on "consensus" sequence information.