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.

Direct digital sensing of protein biomarkers in solution.

The detection of proteins is of central importance to biomolecular analysis and diagnostics. Typical immunosensing assays rely on surface-capture of target molecules, but this constraint can limit specificity, sensitivity, and the ability to obtain information beyond simple concentration measurements. Here we present a surface-free, single-molecule microfluidic sensing platform for direct digital protein biomarker detection in solution, termed digital immunosensor assay (DigitISA). DigitISA is based on microchip electrophoretic separation combined with single-molecule detection and enables absolute number/concentration quantification of proteins in a single, solution-phase step. Applying DigitISA to a range of targets including amyloid aggregates, exosomes, and biomolecular condensates, we demonstrate that the assay provides information beyond stoichiometric interactions, and enables characterization of immunochemistry, binding affinity, and protein biomarker abundance. Taken together, our results suggest a experimental paradigm for the sensing of protein biomarkers, which enables analyses of targets that are challenging to address using conventional immunosensing approaches.

The Chromatin Regulator HMGA1a Undergoes Phase Separation in the Nucleus.

The protein high mobility group A1 (HMGA1) is an important regulator of chromatin organization and function. However, the mechanisms by which it exerts its biological function are not fully understood. Here, we report that the HMGA isoform, HMGA1a, nucleates into foci that display liquid-like properties in the nucleus, and that the protein readily undergoes phase separation to form liquid condensates in vitro. By bringing together machine-leaning modelling, cellular and biophysical experiments and multiscale simulations, we demonstrate that phase separation of HMGA1a is promoted by protein-DNA interactions, and has the potential to be modulated by post-transcriptional effects such as phosphorylation. We further show that the intrinsically disordered C-terminal tail of HMGA1a significantly contributes to its phase separation through electrostatic interactions via AT hooks 2 and 3. Our work sheds light on HMGA1 phase separation as an emergent biophysical factor in regulating chromatin structure.

Biomolecular condensate phase diagrams with a combinatorial microdroplet platform.

The assembly of biomolecules into condensates is a fundamental process underlying the organisation of the intracellular space and the regulation of many cellular functions. Mapping and characterising phase behaviour of biomolecules is essential to understand the mechanisms of condensate assembly, and to develop therapeutic strategies targeting biomolecular condensate systems. A central concept for characterising phase-separating systems is the phase diagram. Phase diagrams are typically built from numerous individual measurements sampling different parts of the parameter space. However, even when performed in microwell plate format, this process is slow, low throughput and requires significant sample consumption. To address this challenge, we present here a combinatorial droplet microfluidic platform, termed PhaseScan, for rapid and high-resolution acquisition of multidimensional biomolecular phase diagrams. Using this platform, we characterise the phase behaviour of a wide range of systems under a variety of conditions and demonstrate that this approach allows the quantitative characterisation of the effect of small molecules on biomolecular phase transitions.

Microchip Free-Flow Electrophoresis for Bioanalysis, Sensing, and Purification.

The separation of complex mixtures is ubiquitous throughout molecular biology, and techniques such as gel-based electrophoresis are common laboratory practice. Such methods are not without their drawbacks, however, which include non-specific interactions between analyte and the separation matrix, poor yields in purification and non-continuous analyte throughput. Microfluidic techniques, which exploit physical phenomena unique to the microscale, promise to improve many aspects of traditional laboratory procedures. These methods offer a quantitative, solution-based alternative to traditional gel electrophoresis, with rapid measurement times enabling the analysis of transient or weak biomolecular interactions that would be challenging to observe with traditional methods. Here, we present a protocol for the lithographic fabrication and operation of microfluidic chips capable of free-flow electrophoretic (FFE) fractionation and analysis of biological analytes. We demonstrate the efficacy of our approach through a protein-sensing methodology based on FFE fractionation of DNA-protein mixtures. In addition, the FFE technique described here can be readily adapted to suit a variety of preparative and analytical applications, providing information on the charge, zeta-potential, and interactions of analytes.

Surface Electrostatics Govern the Emulsion Stability of Biomolecular Condensates.

Liquid-liquid phase separation underlies the formation of biological condensates. Physically, such systems are microemulsions that in general have a propensity to fuse and coalesce; however, many condensates persist as independent droplets in the test tube and inside cells. This stability is crucial for their function, but the physicochemical mechanisms that control the emulsion stability of condensates remain poorly understood. Here, by combining single-condensate zeta potential measurements, optical microscopy, tweezer experiments, and multiscale molecular modeling, we investigate how the nanoscale forces that sustain condensates impact their stability against fusion. By comparing peptide-RNA (PR25:PolyU) and proteinaceous (FUS) condensates, we show that a higher condensate surface charge correlates with a lower fusion propensity. Moreover, measurements of single condensate zeta potentials reveal that such systems can constitute classically stable emulsions. Taken together, these results highlight the role of passive stabilization mechanisms in protecting biomolecular condensates against coalescence.

Liquid-liquid phase separation underpins the formation of replication factories in rotaviruses.

RNA viruses induce the formation of subcellular organelles that provide microenvironments conducive to their replication. Here we show that replication factories of rotaviruses represent protein-RNA condensates that are formed via liquid-liquid phase separation of the viroplasm-forming proteins NSP5 and rotavirus RNA chaperone NSP2. Upon mixing, these proteins readily form condensates at physiologically relevant low micromolar concentrations achieved in the cytoplasm of virus-infected cells. Early infection stage condensates could be reversibly dissolved by 1,6-hexanediol, as well as propylene glycol that released rotavirus transcripts from these condensates. During the early stages of infection, propylene glycol treatments reduced viral replication and phosphorylation of the condensate-forming protein NSP5. During late infection, these condensates exhibited altered material properties and became resistant to propylene glycol, coinciding with hyperphosphorylation of NSP5. Some aspects of the assembly of cytoplasmic rotavirus replication factories mirror the formation of other ribonucleoprotein granules. Such viral RNA-rich condensates that support replication of multi-segmented genomes represent an attractive target for developing novel therapeutic approaches.

Learning the molecular grammar of protein condensates from sequence determinants and embeddings.

Intracellular phase separation of proteins into biomolecular condensates is increasingly recognized as a process with a key role in cellular compartmentalization and regulation. Different hypotheses about the parameters that determine the tendency of proteins to form condensates have been proposed, with some of them probed experimentally through the use of constructs generated by sequence alterations. To broaden the scope of these observations, we established an in silico strategy for understanding on a global level the associations between protein sequence and phase behavior and further constructed machine-learning models for predicting protein liquid-liquid phase separation (LLPS). Our analysis highlighted that LLPS-prone proteins are more disordered, less hydrophobic, and of lower Shannon entropy than sequences in the Protein Data Bank or the Swiss-Prot database and that they show a fine balance in their relative content of polar and hydrophobic residues. To further learn in a hypothesis-free manner the sequence features underpinning LLPS, we trained a neural network-based language model and found that a classifier constructed on such embeddings learned the underlying principles of phase behavior at a comparable accuracy to a classifier that used knowledge-based features. By combining knowledge-based features with unsupervised embeddings, we generated an integrated model that distinguished LLPS-prone sequences both from structured proteins and from unstructured proteins with a lower LLPS propensity and further identified such sequences from the human proteome at a high accuracy. These results provide a platform rooted in molecular principles for understanding protein phase behavior. The predictor, termed DeePhase, is accessible from https://deephase.ch.cam.ac.uk/.

Reentrant liquid condensate phase of proteins is stabilized by hydrophobic and non-ionic interactions.

Liquid-liquid phase separation of proteins underpins the formation of membraneless compartments in living cells. Elucidating the molecular driving forces underlying protein phase transitions is therefore a key objective for understanding biological function and malfunction. Here we show that cellular proteins, which form condensates at low salt concentrations, including FUS, TDP-43, Brd4, Sox2, and Annexin A11, can reenter a phase-separated regime at high salt concentrations. By bringing together experiments and simulations, we demonstrate that this reentrant phase transition in the high-salt regime is driven by hydrophobic and non-ionic interactions, and is mechanistically distinct from the low-salt regime, where condensates are additionally stabilized by electrostatic forces. Our work thus sheds light on the cooperation of hydrophobic and non-ionic interactions as general driving forces in the condensation process, with important implications for aberrant function, druggability, and material properties of biomolecular condensates.

Rapid Structural, Kinetic, and Immunochemical Analysis of Alpha-Synuclein Oligomers in Solution.

Oligomers comprised of misfolded proteins are implicated as neurotoxins in the pathogenesis of protein misfolding conditions such as Parkinson's and Alzheimer's diseases. Structural, biophysical, and biochemical characterization of these nanoscale protein assemblies is key to understanding their pathology and the design of therapeutic interventions, yet it is challenging due to their heterogeneous, transient nature and low relative abundance in complex mixtures. Here, we demonstrate separation of heterogeneous populations of oligomeric α-synuclein, a protein central to the pathology of Parkinson's disease, in solution using microfluidic free-flow electrophoresis. We characterize nanoscale structural heterogeneity of transient oligomers on a time scale of seconds, at least 2 orders of magnitude faster than conventional techniques. Furthermore, we utilize our platform to analyze oligomer ζ-potential and probe the immunochemistry of wild-type α-synuclein oligomers. Our findings contribute to an improved characterization of α-synuclein oligomers and demonstrate the application of microchip electrophoresis for the free-solution analysis of biological nanoparticle analytes.

Von Willebrand factor (vWF): marker of endothelial damage and thrombotic risk in COVID-19?

BACKGROUND: COVID-19 infection is characterised, among other features, by a prothrombotic state with high rate of venous thromboembolism (VTE), D-dimer, and fibrinogen levels. Clinical observations have also highlighted that these patients have elevated von Willebrand factor (vWF) and factor VIIIc. METHODS: 24 consecutive COVID-19 positive patients were selected from the intensive care unit (ICU) or the high acuity ward of Brighton and Sussex University Hospitals NHS Trust. RESULTS: The rate of VTE was 25% and mortality rate was 16.7%. Fibrinogen and D-Dimers were elevated, 7.9 (1.6) g/L and 2.4 (2.02) ug/ml respectively. Factor VIIIc and von vWF antigen levels were both extremely elevated at 279 (148) u/dL and 350 (131) % respectively, which are comparable to levels seen in ICU patients with severe sepsis. vWF levels were significantly higher in patients that died (p=0.017) and showed a positive correlation with age. There was a statistically significant association between COVID-19 disease and non-O blood group (p=0.02); 80% (4/5) of COVID-19 patients with VTE were blood group A. CONCLUSION: Very high levels of vWF and factor VIIIc are common in COVID-19 patients, comparable to levels in severely septic non-COVID ICU patients. This could contribute to the hypercoagulable state and increased VTE rate in COVID-19. Further studies are needed to evaluate the use of vWF for stratifying thrombotic risk in COVID-19 and to determine if elevated vWF is contributing to disease pathogenesis.

Digital Sensing and Molecular Computation by an Enzyme-Free DNA Circuit.

DNA circuits form the basis of programmable molecular systems capable of signal transduction and algorithmic computation. Some classes of molecular programs, such as catalyzed hairpin assembly, enable isothermal, enzyme-free signal amplification. However, current detection limits in DNA amplification circuits are modest, as sensitivity is inhibited by signal leakage resulting from noncatalyzed background reactions inherent to the noncovalent system. Here, we overcome this challenge by optimizing a catalyzed hairpin assembly for single-molecule sensing in a digital droplet assay. Furthermore, we demonstrate digital reporting of DNA computation at the single-molecule level by employing ddCHA as a signal transducer for simple DNA logic gates. By facilitating signal transduction of molecular computation at pM concentration, our approach can improve processing density by a factor of 104 relative to conventional DNA logic gates. More broadly, we believe that digital molecular computing will broaden the scope and efficacy of isothermal amplification circuits within DNA computing, biosensing, and signal amplification in general.

Microfluidic approaches for the analysis of protein-protein interactions in solution.

Exploration and characterisation of the human proteome is a key objective enabling a heightened understanding of biological function, malfunction and pharmaceutical design. Since proteins typically exhibit their behaviour by binding to other proteins, the challenge of probing protein-protein interactions has been the focus of new and improved experimental approaches. Here, we review recently developed microfluidic techniques for the study and quantification of protein-protein interactions. We focus on methodologies that utilise the inherent strength of microfluidics for the control of mass transport on the micron scale, to facilitate surface and membrane-free interrogation and quantification of interacting proteins. Thus, the microfluidic tools described here provide the capability to yield insights on protein-protein interactions under physiological conditions. We first discuss the defining principles of microfluidics, and methods for the analysis of protein-protein interactions that utilise the diffusion-controlled mixing characteristic of fluids at the microscale. We then describe techniques that employ electrophoretic forces to manipulate and fractionate interacting protein systems for their biophysical characterisation, before discussing strategies that use microdroplet compartmentalisation for the analysis of protein interactions. We conclude by highlighting future directions for the field, such as the integration of microfluidic experiments into high-throughput workflows for the investigation of protein interaction networks.

Combining Affinity Selection and Specific Ion Mobility for Microchip Protein Sensing.

The sensitive detection of proteins is a key objective in many areas of biomolecular science, ranging from biophysics to diagnostics. However, sensing in complex biological fluids is hindered by nonspecific interactions with off-target species. Here, we describe and demonstrate an assay that utilizes both the chemical and physical properties of the target species to achieve high selectivity in a manner not possible by chemical complementarity alone, in complex media. We achieve this objective through a combinatorial strategy, by simultaneously exploiting free-flow electrophoresis for target selection, on the basis of electrophoretic mobility, and conventional affinity-based selection. In addition, we demonstrate amplification of the resultant signal by a catalytic DNA nanocircuit. This approach brings together the inherent solution-phase advantages of microfluidic sample handling with isothermal, enzyme-free signal amplification. With this method, no surface immobilization or washing steps are required, and our assay is well suited to monoepitopic targets, presenting advantages over conventional ELISA techniques.