The binding of the small heat-shock protein αB-crystallin to fibrils of α-synuclein is driven by entropic forces.

Molecular chaperones are key components of the cellular proteostasis network whose role includes the suppression of the formation and proliferation of pathogenic aggregates associated with neurodegenerative diseases. The molecular principles that allow chaperones to recognize misfolded and aggregated proteins remain, however, incompletely understood. To address this challenge, here we probe the thermodynamics and kinetics of the interactions between chaperones and protein aggregates under native solution conditions using a microfluidic platform. We focus on the binding between amyloid fibrils of α-synuclein, associated with Parkinson's disease, to the small heat-shock protein αB-crystallin, a chaperone widely involved in the cellular stress response. We find that αB-crystallin binds to α-synuclein fibrils with high nanomolar affinity and that the binding is driven by entropy rather than enthalpy. Measurements of the change in heat capacity indicate significant entropic gain originates from the disassembly of the oligomeric chaperones that function as an entropic buffer system. These results shed light on the functional roles of chaperone oligomerization and show that chaperones are stored as inactive complexes which are capable of releasing active subunits to target aberrant misfolded species.

Single-Molecule Sizing through Nanocavity Confinement.

An approach relying on nanocavity confinement is developed in this paper for the sizing of nanoscale particles and single biomolecules in solution. The approach, termed nanocavity diffusional sizing (NDS), measures particle residence times within nanofluidic cavities to determine their hydrodynamic radii. Using theoretical modeling and simulations, we show that the residence time of particles within nanocavities above a critical time scale depends on the diffusion coefficient of the particle, which allows the estimation of the particle's size. We demonstrate this approach experimentally through the measurement of particle residence times within nanofluidic cavities using single-molecule confocal microscopy. Our data show that the residence times scale linearly with the sizes of nanoscale colloids, protein aggregates, and single DNA oligonucleotides. NDS thus constitutes a new single molecule optofluidic approach that allows rapid and quantitative sizing of nanoscale particles for potential applications in nanobiotechnology, biophysics, and clinical diagnostics.

Thermodynamic profiles for cotranslational trigger factor substrate recognition.

Molecular chaperones are central to the maintenance of proteostasis in living cells. A key member of this protein family is trigger factor (TF), which acts throughout the protein life cycle and has a ubiquitous role as the first chaperone encountered by proteins during synthesis. However, our understanding of how TF achieves favorable interactions with such a diverse substrate base remains limited. Here, we use microfluidics to reveal the thermodynamic determinants of this process. We find that TF binding to empty 70S ribosomes is enthalpy-driven, with micromolar affinity, while nanomolar affinity is achieved through a favorable entropic contribution for both intrinsically disordered and folding-competent nascent chains. These findings suggest a general mechanism for cotranslational TF function, which relies on occupation of the exposed TF-substrate binding groove rather than specific complementarity between chaperone and nascent chain. These insights add to our wider understanding of how proteins can achieve broad substrate specificity.

α-Synuclein Oligomers Displace Monomeric α-Synuclein from Lipid Membranes.

Parkinson's disease (PD) is an increasingly prevalent and currently incurable neurodegenerative disorder linked to the accumulation of α-synuclein (αS) protein aggregates in the nervous system. While αS binding to membranes in its monomeric state is correlated to its physiological role, αS oligomerization and subsequent aberrant interactions with lipid bilayers have emerged as key steps in PD-associated neurotoxicity. However, little is known of the mechanisms that govern the interactions of oligomeric αS (OαS) with lipid membranes and the factors that modulate such interactions. This is in large part due to experimental challenges underlying studies of OαS-membrane interactions due to their dynamic and transient nature. Here, we address this challenge by using a suite of microfluidics-based assays that enable in-solution quantification of OαS-membrane interactions. We find that OαS bind more strongly to highly curved, rather than flat, lipid membranes. By comparing the membrane-binding properties of OαS and monomeric αS (MαS), we further demonstrate that OαS bind to membranes with up to 150-fold higher affinity than their monomeric counterparts. Moreover, OαS compete with and displace bound MαS from the membrane surface, suggesting that disruption to the functional binding of MαS to membranes may provide an additional toxicity mechanism in PD. These findings present a binding mechanism of oligomers to model membranes, which can potentially be targeted to inhibit the progression of PD.

Single-molecule digital sizing of proteins in solution.

The physical characterization of proteins in terms of their sizes, interactions, and assembly states is key to understanding their biological function and dysfunction. However, this has remained a difficult task because proteins are often highly polydisperse and present as multicomponent mixtures. Here, we address this challenge by introducing single-molecule microfluidic diffusional sizing (smMDS). This approach measures the hydrodynamic radius of single proteins and protein assemblies in microchannels using single-molecule fluorescence detection. smMDS allows for ultrasensitive sizing of proteins down to femtomolar concentrations and enables affinity profiling of protein interactions at the single-molecule level. We show that smMDS is effective in resolving the assembly states of protein oligomers and in characterizing the size of protein species within complex mixtures, including fibrillar protein aggregates and nanoscale condensate clusters. Overall, smMDS is a highly sensitive method for the analysis of proteins in solution, with wide-ranging applications in drug discovery, diagnostics, and nanobiotechnology.

Microscale Diffusiophoresis of Proteins.

Living systems are characterized by their spatially highly inhomogeneous nature which is susceptible to modify fundamentally the behavior of biomolecular species, including the proteins that underpin biological functionality in cells. Spatial gradients in chemical potential are known to lead to strong transport effects for colloidal particles, but their effect on molecular scale species such as proteins has remained largely unexplored. Here, we improve on existing diffusiophoresis microfluidic technique to measure protein diffusiophoresis in real space. The measurement of proteins is made possible by two ameliorations. First, a label-free microscope is used to suppress label interference. Second, improvements in numerical methods are developed to meet the particular challenges posed by small molecules. We demonstrate that individual proteins can undergo strong diffusiophoretic motion in salt gradients in a manner which is sufficient to overcome diffusion and which leads to dramatic changes in their spatial organization on the scale of a cell. Moreover, we demonstrate that this phenomenon can be used to control the motion of proteins in microfluidic devices. These results open up a path towards a physical understanding of the role of gradients in living systems in the spatial organization of macromolecules and highlight novel routes towards protein sorting applications on device.

Machine learning-aided protein identification from multidimensional signatures.

The ability to determine the identity of specific proteins is a critical challenge in many areas of cellular and molecular biology, and in medical diagnostics. Here, we present a macine learning aided microfluidic protein characterisation strategy that within a few minutes generates a three-dimensional fingerprint of a protein sample indicative of its amino acid composition and size and, thereby, creates a unique signature for the protein. By acquiring such multidimensional fingerprints for a set of ten proteins and using machine learning approaches to classify the fingerprints, we demonstrate that this strategy allows proteins to be classified at a high accuracy, even though classification using a single dimension is not possible. Moreover, we show that the acquired fingerprints correlate with the amino acid content of the samples, which makes it is possible to identify proteins directly from their sequence without requiring any prior knowledge about the fingerprints. These findings suggest that such a multidimensional profiling strategy can lead to the development of a novel method for protein identification in a microfluidic format.

The Hsc70 disaggregation machinery removes monomer units directly from α-synuclein fibril ends.

Molecular chaperones contribute to the maintenance of cellular protein homoeostasis through assisting de novo protein folding and preventing amyloid formation. Chaperones of the Hsp70 family can further disaggregate otherwise irreversible aggregate species such as α-synuclein fibrils, which accumulate in Parkinson's disease. However, the mechanisms and kinetics of this key functionality are only partially understood. Here, we combine microfluidic measurements with chemical kinetics to study α-synuclein disaggregation. We show that Hsc70 together with its co-chaperones DnaJB1 and Apg2 can completely reverse α-synuclein aggregation back to its soluble monomeric state. This reaction proceeds through first-order kinetics where monomer units are removed directly from the fibril ends with little contribution from intermediate fibril fragmentation steps. These findings extend our mechanistic understanding of the role of chaperones in the suppression of amyloid proliferation and in aggregate clearance, and inform on possibilities and limitations of this strategy in the development of therapeutics against synucleinopathies.

A microfluidic strategy for the detection of membrane protein interactions.

Membrane proteins perform a vast range of vital biological functions and are the gatekeepers for exchange of information and matter between the intracellular and extracellular environment. However, membrane protein interactions can be challenging to characterise in a quantitative manner due to the low solubility and large size of the membrane protein complex with associated lipid or detergent molecules. Here, we show that measurements of the changes in charge and diffusivity on the micron scale allow for non-disruptive studies of membrane protein interactions in solution. The approach presented here uses measurements of key physical properties of membrane proteins and their ligands to characterise the binding equilibrium parameters. We demonstrate this approach for human aquaporins (AQPs), key membrane proteins in the regulation of water homeostasis in cells. We perform quantitative measurements to characterise the interactions between two full-length AQP isoforms and the regulatory protein, calmodulin (CaM), and show that CaM selectively binds AQP0. Through direct measurements of the diffusivity and mobility in an external electric field, the diffusion coefficients and electrophoretic mobilities are determined for the individual components and the resulting AQP0-CaM complex. Furthermore, we obtain directly the binding equilibrium parameters and effective charge of each component. These results open up a route towards the use of microfluidics as a general platform in protein science and open up new possibilities for the characterisation of membrane protein interactions in solution.