Phase-separating RNA-binding proteins form heterogeneous distributions of clusters in subsaturated solutions

Macromolecular phase separation is thought to be one of the processes that drives the formation of membraneless biomolecular condensates in cells. The dynamics of phase separation are thought to follow the tenets of classical nucleation theory, and, therefore, subsaturated solutions should be devoid of clusters with more than a few molecules. We tested this prediction using in vitro biophysical studies to characterize subsaturated solutions of phase-separating RNA-binding proteins with intrinsically disordered prion-like domains and RNA-binding domains. Surprisingly, and in direct contradiction to expectations from classical nucleation theory, we find that subsaturated solutions are characterized by the presence of heterogeneous distributions of clusters. The distributions of cluster sizes, which are dominated by small species, shift continuously toward larger sizes as protein concentrations increase and approach the saturation concentration. As a result, many of the clusters encompass tens to hundreds of molecules, while less than 1% of the solutions are mesoscale species that are several hundred nanometers in diameter. We find that cluster formation in subsaturated solutions and phase separation in supersaturated solutions are strongly coupled via sequence-encoded interactions. We also find that cluster formation and phase separation can be decoupled using solutes as well as specific sets of mutations. Our findings, which are concordant with predictions for associative polymers, implicate an interplay between networks of sequence-specific and solubility-determining interactions that, respectively, govern cluster formation in subsaturated solutions and the saturation concentrations above which phase separation occurs.

Phase-separating RNA-binding proteins form heterogeneous distributions of clusters in subsaturated solutions

Macromolecular phase separation is thought to be one of the processes that drives the formation of membraneless biomolecular condensates in cells. The dynamics of phase separation are thought to follow the tenets of classical nucleation theory, and, therefore, subsaturated solutions should be devoid of clusters with more than a few molecules. We tested this prediction using in vitro biophysical studies to characterize subsaturated solutions of phase-separating RNA-binding proteins with intrinsically disordered prion-like domains and RNA-binding domains. Surprisingly, and in direct contradiction to expectations from classical nucleation theory, we find that subsaturated solutions are characterized by the presence of heterogeneous distributions of clusters. The distributions of cluster sizes, which are dominated by small species, shift continuously toward larger sizes as protein concentrations increase and approach the saturation concentration. As a result, many of the clusters encompass tens to hundreds of molecules, while less than 1% of the solutions are mesoscale species that are several hundred nanometers in diameter. We find that cluster formation in subsaturated solutions and phase separation in supersaturated solutions are strongly coupled via sequence-encoded interactions. We also find that cluster formation and phase separation can be decoupled using solutes as well as specific sets of mutations. Our findings, which are concordant with predictions for associative polymers, implicate an interplay between networks of sequence-specific and solubility-determining interactions that, respectively, govern cluster formation in subsaturated solutions and the saturation concentrations above which phase separation occurs.

Mechanistic Models of Protein Aggregation Across Length-Scales and Time-Scales: From the Test Tube to Neurodegenerative Disease

Through advances in the past decades, the central role of aberrant protein aggregation has been established in many neurodegenerative diseases. Crucially, however, the molecular mechanisms that underlie aggregate proliferation in the brains of affected individuals are still only poorly understood. Under controlled in vitro conditions, significant progress has been made in elucidating the molecular mechanisms that take place during the assembly of purified protein molecules, through advances in both experimental methods and the theories used to analyse the resulting data. The determination of the aggregation mechanism for a variety of proteins revealed the importance of intermediate oligomeric species and of the interactions with promotors and inhibitors. Such mechanistic insights, if they can be achieved in a disease-relevant system, provide invaluable information to guide the design of potential cures to these devastating disorders. However, as experimental systems approach the situation present in real disease, their complexity increases substantially. Timescales increase from hours an aggregation reaction takes in vitro, to decades over which the process takes place in disease, and length-scales increase to the dimension of a human brain. Thus, molecular level mechanistic studies, like those that successfully determined mechanisms in vitro, have only been applied in a handful of living systems to date. If their application can be extended to further systems, including patient data, they promise powerful new insights. Here we present a review of the existing strategies to gain mechanistic insights into the molecular steps driving protein aggregation and discuss the obstacles and potential paths to achieving their application in disease. First, we review the experimental approaches and analysis techniques that are used to establish the aggregation mechanisms in vitro and the insights that have been gained from them. We then discuss how these approaches must be modified and adapted to be applicable in vivo and review the existing works that have successfully applied mechanistic analysis of protein aggregation in living systems. Finally, we present a broad mechanistic classification of in vivo systems and discuss what will be required to further our understanding of aggregate formation in living systems.

Kinetic profiling of therapeutic strategies for inhibiting the formation of amyloid oligomers

Protein self-assembly into amyloid fibrils underlies several neurodegenerative conditions, including Alzheimer's and Parkinson's diseases. It has become apparent that the small oligomers formed during this process constitute neurotoxic molecular species associated with amyloid aggregation. Targeting the formation of oligomers represents, therefore, a possible therapeutic avenue to combat these diseases. However, it remains challenging to establish which microscopic steps should be targeted to suppress most effectively the generation of oligomeric aggregates. Recently, we have developed a kinetic model of oligomer dynamics during amyloid aggregation. Here, we use this approach to derive explicit scaling relationships that reveal how key features of the time evolution of oligomers, including oligomer peak concentration and lifetime, are controlled by the different rate parameters. We discuss the therapeutic implications of our framework by predicting changes in oligomer concentrations when the rates of the individual microscopic events are varied. Our results identify the kinetic parameters that control most effectively the generation of oligomers, thus opening a new path for the systematic rational design of therapeutic strategies against amyloid-related diseases.

Microfluidic Antibody Affinity Profiling Reveals the Role of Memory Reactivation and Cross-Reactivity in the Defense Against SARS-CoV-2

Recent efforts in understanding the course and severity of SARS-CoV-2 infections have highlighted both potentially beneficial and detrimental effects of cross-reactive antibodies derived from memory immunity. Specifically, due to a significant degree of sequence similarity between SARS-CoV-2 and other members of the coronavirus family, memory B-cells that emerged from previous infections with endemic human coronaviruses (HCoVs) could be reactivated upon encountering the newly emerged SARS-CoV-2, thus prompting the production of cross-reactive antibodies. Determining the affinity and concentration of these potentially cross-reactive antibodies to the new SARS-CoV-2 antigens is therefore particularly important when assessing both existing immunity against common HCoVs and adverse effects like antibody-dependent enhancement (ADE) in COVID-19. However, these two fundamental parameters cannot easily be disentangled by surface-based assays like enzyme-linked immunosorbent assays (ELISAs), which are routinely used to assess cross-reactivity. Here, we have used microfluidic antibody affinity profiling (MAAP) to quantitatively evaluate the humoral immune response in COVID-19 convalescent patients by determining both antibody affinity and concentration against spike antigens of SARS-CoV-2 directly in nine convalescent COVID-19 patient and three pre-pandemic sera that were seropositive for common HCoVs. All 12 sera contained low concentrations of high-affinity antibodies against spike antigens of HCoV-NL63 and HCoV-HKU1, indicative of past exposure to these pathogens, while the affinity against the SARS-CoV-2 spike protein was lower. These results suggest that cross-reactivity as a consequence of memory reactivation upon an acute SARS-CoV-2 infection may not be a significant factor in generating immunity against SARS-CoV-2.

The Pathological G51D Mutation in Alpha-Synuclein Oligomers Confers Distinct Structural Attributes and Cellular Toxicity

A wide variety of oligomeric structures are formed during the aggregation of proteins associated with neurodegenerative diseases. Such soluble oligomers are believed to be key toxic species in the related disorders; therefore, identification of the structural determinants of toxicity is of upmost importance. Here, we analysed toxic oligomers of α-synuclein and its pathological variants in order to identify structural features that could be related to toxicity and found a novel structural polymorphism within G51D oligomers. These G51D oligomers can adopt a variety of β-sheet-rich structures with differing degrees of α-helical content, and the helical structural content of these oligomers correlates with the level of induced cellular dysfunction in SH-SY5Y cells. This structure–function relationship observed in α-synuclein oligomers thus presents the α-helical structure as another potential structural determinant that may be linked with cellular toxicity in amyloid-related proteins.

The C-terminal tail of α-synuclein protects against aggregate replication but is critical for oligomerization

Aggregation of the 140-residue protein α-synuclein (αSN) is a key factor in the etiology of Parkinson’s disease. Although the intensely anionic C-terminal domain (CTD) of αSN does not form part of the amyloid core region or affect membrane binding ability, truncation or reduction of charges in the CTD promotes fibrillation through as yet unknown mechanisms. Here, we study stepwise truncated CTDs and identify a threshold region around residue 121; constructs shorter than this dramatically increase their fibrillation tendency. Remarkably, these effects persist even when as little as 10% of the truncated variant is mixed with the full-length protein. Increased fibrillation can be explained by a substantial increase in self-replication, most likely via fragmentation. Paradoxically, truncation also suppresses toxic oligomer formation, and oligomers that can be formed by chemical modification show reduced membrane affinity and cytotoxicity. These remarkable changes correlate to the loss of negative electrostatic potential in the CTD and highlight a double-edged electrostatic safety guard.

Farzadfard et al. present a comprehensive analysis of a range of C-terminal truncations of aSN, linking the importance of high C-terminus charge for decreased fibrillation rates. The ability to formation oligomers, to disrupt synthetic vesicles and cell toxicity was reduced with truncated aSN, aiding in understanding of the intramolecular interactions of aSN which promote/inhibit aggregation.

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.

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.

Proliferation of Tau 304-380 Fragment Aggregates through Autocatalytic Secondary Nucleation

The self-assembly of the protein tau into neurofibrillary tangles is one of the hallmarks of Alzheimer’s disease and related tauopathies. Still, the molecular mechanism of tau aggregation is largely unknown. This problem may be addressed by systematically obtaining reproducible in vitro kinetics measurements under quiescent conditions in the absence of triggering substances. Here, we implement this strategy by developing protocols for obtaining an ultrapure tau fragment (residues 304–380 of tau441) and for performing spontaneous aggregation assays with reproducible kinetics under quiescent conditions. We are thus able to identify the mechanism of fibril formation of the tau 304–380 fragment at physiological pH using fluorescence spectroscopy and mass spectrometry. We find that primary nucleation is slow, and that secondary processes dominate the aggregation process once the initial aggregates are formed. Moreover, our results further show that secondary nucleation of monomers on fibril surfaces dominates over fragmentation of fibrils. Using separate isotopes in monomers and fibrils, through mass spectroscopy measurements, we verify the isotope composition of the intermediate oligomeric species, which reveals that these small aggregates are generated from monomer through secondary nucleation. Our results provide a framework for understanding the processes leading to tau aggregation in disease and for selecting possible tau forms as targets in the development of therapeutic interventions in Alzheimer’s disease.

Kinetic and Thermodynamic Driving Factors in the Assembly of Phenylalanine-Based Modules

The formation of ordered protein and peptide assemblies is a phenomenon related to a wide range of human diseases. However, the mechanism of assembly at the molecular level remains largely unknown. Minimal models enable the exploration of the underlying interactions that are at the core of such self-assembly processes. In particular, the ability of phenylalanine, a single aromatic amino acid, to form an amyloid-like structure has challenged the previous dogma viewing a peptide backbone as a prerequisite for assembly. The driving forces controlling the nucleation and assembly in the absence of a peptide backbone remain to be identified. Here, aiming to unravel these forces, we explored the kinetics and thermodynamics of three phenylalanine-containing molecules during their assembly process: the amino acid phenylalanine, which accumulates in phenylketonuria patients, the diphenylalanine core-motif of the amyloid β peptide related to Alzheimer's disease, and the extended triphenylalanine peptide which forms a range of distinct nanostructures in vitro. We found that the aggregation propensity, regarding the critical monomer concentration, strongly increases with size, with triphenylalanine being the most aggregation-prone species under our experimental conditions. In the context of classical nucleation theory, this increase in aggregation propensity can be attributed to the larger free energy decrease upon aggregation of larger peptides and is not due to the presence/absence of a peptide bond per se. Taken together, this work provides insights into the aggregation processes of chemically simple systems and suggests that both backbone-containing peptides and backbone-lacking amino acids assemble through a similar mechanism, thus supporting the classification of amino acids in the continuum of amyloid-forming building blocks.

Surface-Catalyzed Secondary Nucleation Dominates the Generation of Toxic IAPP Aggregates

The aggregation of the human islet amyloid polypeptide (IAPP) is associated with diabetes type II. A quantitative understanding of this connection at the molecular level requires that the aggregation mechanism of IAPP is resolved in terms of the underlying microscopic steps. Here we have systematically studied recombinant IAPP, with amidated C-terminus in oxidised form with a disulphide bond between residues 3 and 7, using thioflavin T fluorescence to monitor the formation of amyloid fibrils as a function of time and IAPP concentration. We used global kinetic analyses to connect the macroscopic measurements of aggregation to the microscopic mechanisms, and show that the generation of new aggregates is dominated by the secondary nucleation of monomers on the fibril surface. We then exposed insulinoma cells to aliquots extracted from different time points of the aggregation process, finding the highest toxicity at the midpoint of the reaction, when the secondary nucleation rate reaches its maximum. These results identify IAPP oligomers as the most cytotoxic species generated during IAPP aggregation, and suggest that compounds that target secondary nucleation of IAPP could be most effective as therapeutic candidates for diabetes type II.

In vivo rate-determining steps of tau seed accumulation in Alzheimer's disease

Both the replication of protein aggregates and their spreading throughout the brain are implicated in the progression of Alzheimer’s disease (AD). However, the rates of these processes are unknown and the identity of the rate-determining process in humans has therefore remained elusive. By bringing together chemical kinetics with measurements of tau seeds and aggregates across brain regions, we can quantify their replication rate in human brains. Notably, we obtain comparable rates in several different datasets, with five different methods of tau quantification, from postmortem seed amplification assays to tau PET studies in living individuals. Our results suggest that from Braak stage III onward, local replication, rather than spreading between brain regions, is the main process controlling the overall rate of accumulation of tau in neocortical regions. The number of seeds doubles only every ∼5 years. Thus, limiting local replication likely constitutes the most promising strategy to control tau accumulation during AD.

Squalamine and trodusquemine: two natural products for neurodegenerative diseases, from physical chemistry to the clinic

Covering: 1993 to 2021 (mainly 2017-2021)Alzheimer's and Parkinson's diseases are neurodegenerative conditions affecting over 50 million people worldwide. Since these disorders are still largely intractable pharmacologically, discovering effective treatments is of great urgency and importance. These conditions are characteristically associated with the aberrant deposition of proteinaceous aggregates in the brain, and with the formation of metastable intermediates known as protein misfolded oligomers that play a central role in their aetiology. In this Highlight article, we review the evidence at the physicochemical, cellular, animal model and clinical levels on how the natural products squalamine and trodusquemine offer promising opportunities for chronic treatments for these progressive conditions by preventing both the formation of neurotoxic oligomers and their interaction with cell membranes.

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.

Accelerating Reaction Rates of Biomolecules by Using Shear Stress in Artificial Capillary Systems

Biomimetics is a design principle within chemistry, biology, and engineering, but chemistry biomimetic approaches have been generally limited to emulating nature's chemical toolkit while emulation of nature's physical toolkit has remained largely unexplored. To begin to explore this, we designed biophysically mimetic microfluidic reactors with characteristic length scales and shear stresses observed within capillaries. We modeled the effect of shear with molecular dynamics studies and showed that this induces specific normally buried residues to become solvent accessible. We then showed using kinetics experiments that rates of reaction of these specific residues in fact increase in a shear-dependent fashion. We applied our results in the creation of a new microfluidic approach for the multidimensional study of cysteine biomarkers. Finally, we used our approach to establish dissociation of the therapeutic antibody trastuzumab in a reducing environment. Our results have implications for the efficacy of existing therapeutic antibodies in blood plasma as well as suggesting in general that biophysically mimetic chemistry is exploited in biology and should be explored as a research area.

Mechanism of Secondary Nucleation at the Single Fibril Level from Direct Observations of Aβ42 Aggregation

The formation of amyloid fibrils and oligomers is a hallmark of several neurodegenerative disorders, including Alzheimer's disease (AD), and contributes to the disease pathway. To progress our understanding of these diseases at a molecular level, it is crucial to determine the mechanisms and rates of amyloid formation and replication. In the context of AD, the self-replication of aggregates of the Aβ42 peptide by secondary nucleation, leading to the formation of new aggregates on the surfaces of existing ones, is a major source of both new fibrils and smaller toxic oligomeric species. However, the core mechanistic determinants, including the presence of intermediates, as well as the role of heterogeneities in the fibril population, are challenging to determine from bulk aggregation measurements. Here, we obtain such information by monitoring directly the time evolution of individual fibrils by TIRF microscopy. Crucially, essentially all aggregates have the ability to self-replicate via secondary nucleation, and the amplification of the aggregate concentration cannot be explained by a small fraction of "superspreader" fibrils. We observe that secondary nucleation is a catalytic multistep process involving the attachment of soluble species to the fibril surface, followed by conversion/detachment to yield a new fibril in solution. Furthermore, we find that fibrils formed by secondary nucleation resemble the parent fibril population. This detailed level of mechanistic insights into aggregate self-replication is key in the rational design of potential inhibitors of this process.

New Frontiers for Machine Learning in Protein Science

Protein function is fundamentally reliant on inter-molecular interactions that underpin the ability of proteins to form complexes driving biological processes in living cells. Increasingly, such interactions are recognised as being formed between proteins that exist on a broad spectrum of dynamic conformational states and levels of intrinsic disorder. Additionally, the sizes of the structures formed can range from simple binary complexes to large dynamic biomolecular condensates measuring 100 nm or more. Understanding the parameters that govern such interactions, how they form, how they lead to function and what happens when they take place in unintended manners and lead to disease, represent some of the core questions for molecular biosciences. In light of recent advances made in solving the protein folding problem by machine learning methods, we discuss here the challenges and opportunities brought by these new data-driven approaches for the next frontiers of biomolecular science.

Sequential storage and release of microdroplets

Droplet microfluidic methods have opened up the possibility of studying a plethora of phenomena ranging from biological to physical or chemical processes at ultra low volumes and high throughput. A key component of such approaches is the ability to trap droplets for observation, and many device architectures for achieving this objective have been developed. A challenge with such approaches is, however, recovering the droplets following their confinement for applications involving further analysis. Here, we present a device capable of generating, confining and releasing microdroplets in a sequential manner. Through a combination of experimental and computational simulations, we shed light on the key features required for successful droplet storage and retrieval. Moreover, we explore the effect of the flow rate of the continuous phase on droplet release, determining that a critical rate is needed to ensure complete droplet deformation through constrictions holding the droplets in place prior to release. Finally, we find that once released, droplets can be retrieved and collected off chip. The ability to generate, store and sequentially release droplets renders such a device particularly promising for future applications where reactions may not only be monitored on-chip, but droplets can also be retrieved for further analysis, facilitating new exploratory avenues in the fields of analytical chemistry and biology.

LAG3 is not expressed in human and murine neurons and does not modulate α-synucleinopathies

While the initial pathology of Parkinson's disease and other α-synucleinopathies is often confined to circumscribed brain regions, it can spread and progressively affect adjacent and distant brain locales. This process may be controlled by cellular receptors of α-synuclein fibrils, one of which was proposed to be the LAG3 immune checkpoint molecule. Here, we analysed the expression pattern of LAG3 in human and mouse brains. Using a variety of methods and model systems, we found no evidence for LAG3 expression by neurons. While we confirmed that LAG3 interacts with α-synuclein fibrils, the specificity of this interaction appears limited. Moreover, overexpression of LAG3 in cultured human neural cells did not cause any worsening of α-synuclein pathology ex vivo. The overall survival of A53T α-synuclein transgenic mice was unaffected by LAG3 depletion, and the seeded induction of α-synuclein lesions in hippocampal slice cultures was unaffected by LAG3 knockout. These data suggest that the proposed role of LAG3 in the spreading of α-synucleinopathies is not universally valid.

Conformational Expansion of Tau in Condensates Promotes Irreversible Aggregation

Liquid-liquid phase separation (LLPS) of proteins into biomolecular condensates has emerged as a fundamental principle underpinning cellular function and malfunction. Indeed, many human pathologies, including protein misfolding diseases, are linked to aberrant liquid-to-solid phase transitions, and disease-associated protein aggregates often nucleate through phase separation. The molecular level determinants that promote pathological phase transitions remain, however, poorly understood. Here we study LLPS of the microtubule-associated protein Tau, whose aberrant aggregation is associated with a number of neurodegenerative diseases, including Alzheimer's disease. Using single molecule spectroscopy, we probe directly the conformational changes that the protein undergoes as a result of LLPS. We perform single-molecule FRET and fluorescence correlation spectroscopy experiments to monitor the intra- and intermolecular changes and demonstrate that the N- and C-terminal regions of Tau become extended, thus exposing the microtubule-binding region. These changes facilitate intermolecular interactions and allow for the formation of nanoscale clusters of Tau. Our results suggest that these clusters can promote the fibrillization of Tau, which can be dramatically accelerated by disease-related mutations P301L and P301S. Our findings thus provide important molecular insights into the mechanism of protein phase separation and the conversion of protein condensates from functional liquid assemblies to pathological aggregates.

Unraveling the Physicochemical Determinants of Protein Liquid-liquid Phase Separation by Nanoscale Infrared Vibrational Spectroscopy

The phenomenon of reversible liquid-liquid phase separation of proteins underlies the formation of membraneless organelles, which are crucial for cellular processes such as signalling and transport. In addition, it is also of great interest to uncover the mechanisms of further irreversible maturation of the functional dense liquid phase into aberrant insoluble assemblies due to its implication in human disease. Recent advances in methods based on atomic force microscopy (AFM) have made it possible to study protein condensates at the nanometer level, providing unprecedented information on the nature of the intermolecular interactions governing phase separation. Here, we provide an in-depth description of a protocol for the characterisation of the morphology, stiffness, and chemical properties of protein condensates using infrared nanospectroscopy (AFM-IR).

Feedback control of protein aggregation

The self-assembly of peptides and proteins into amyloid fibrils plays a causative role in a wide range of increasingly common and currently incurable diseases. The molecular mechanisms underlying this process have recently been discovered, prompting the development of drugs that inhibit specific reaction steps as possible treatments for some of these disorders. A crucial part of treatment design is to determine how much drug to give and when to give it, informed by its efficacy and intrinsic toxicity. Since amyloid formation does not proceed at the same pace in different individuals, it is also important that treatment design is informed by local measurements of the extent of protein aggregation. Here, we use stochastic optimal control theory to determine treatment regimens for inhibitory drugs targeting several key reaction steps in protein aggregation, explicitly taking into account variability in the reaction kinetics. We demonstrate how these regimens may be updated "on the fly" as new measurements of the protein aggregate concentration become available, in principle, enabling treatments to be tailored to the individual. We find that treatment timing, duration, and drug dosage all depend strongly on the particular reaction step being targeted. Moreover, for some kinds of inhibitory drugs, the optimal regimen exhibits high sensitivity to stochastic fluctuations. Feedback controls tailored to the individual may therefore substantially increase the effectiveness of future treatments.

Antibody Affinity Governs the Inhibition of SARS-CoV-2 Spike/ACE2 Binding in Patient Serum

The humoral immune response plays a key role in suppressing the pathogenesis of SARS-CoV-2. The molecular determinants underlying the neutralization of the virus remain, however, incompletely understood. Here, we show that the ability of antibodies to disrupt the binding of the viral spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor on the cell, the key molecular event initiating SARS-CoV-2 entry into host cells, is controlled by the affinity of these antibodies to the viral antigen. By using microfluidic antibody-affinity profiling, we were able to quantify the serum-antibody mediated inhibition of ACE2-spike binding in two SARS-CoV-2 seropositive individuals. Measurements to determine the affinity, concentration, and neutralization potential of antibodies were performed directly in human serum. Using this approach, we demonstrate that the level of inhibition in both samples can be quantitatively described using the dissociation constants (KD) of the binary interactions between the ACE2 receptor and the spike protein as well as the spike protein and the neutralizing antibody. These experiments represent a new type of in-solution receptor binding competition assay, which has further potential applications, ranging from decisions on donor selection for convalescent plasma therapy, to identification of lead candidates in therapeutic antibody development, and vaccine development.

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.