Biology subjects

Krainer, G.

Publications and source records attributed to Krainer, G..

25 records · Page 2Linked to original sources

bioRxiv2020

The Hsc70 Disaggregation Machinery RemovesMonomer Units Directly from α-Synuclein FibrilEnds

Molecular chaperones contribute to the maintenance of cellular protein homeostasis through a wide range of mechanisms, including the assistance of de novo protein folding, the rescue of misfolded proteins, and the prevention of amyloid formation. Chaperones of the Hsp70 family have a striking capability of disaggregating otherwise irreversible aggregate structures such as amyloid fibrils that accumulate during the development of neurodegenerative diseases. However, the mechanisms of this key emerging functionality remain largely unknown. Here, we bring together microfluidic measurements with kinetic analysis and show that that the Hsp70 protein heat chock complement Hsc70 together with its two co-chaperones DnaJB1 and the nucleotide exchange factor Apg2 is able to completely reverse the aggregation process of alpha-synuclein, associated with Parkinsons disease, back to its soluble monomeric state. Moreover, we show that this reaction proceeds with first order kinetics in a process where monomer units are taken off directly from the fibril ends. Our results demonstrate that all components of the chaperone triad are essential for fibril disaggregation. Lastly, we quantify the interactions between the three chaperones as well as between the chaperones and the fibrils in solution, yielding both binding stoichiometries and dissociation constants. Crucially, we find that the stoichiometry of Hsc70 binding to fibrils suggests Hsc70 clustering at the fibril ends. Taken together, our results show that the mechanism of action of the Hsc70-DnaJB1-Apg2 chaperone system in disaggregating -synuclein fibrils involves the removal of monomer units without any intermediate fragmentation steps. These findings are fundamental to our understanding of the suppression of amyloid proliferation early in life and the natural clearance mechanisms of fibrillar deposits in Parkinsons disease, and inform on the possibilities and limitations of this strategy in the development of therapeutics against synucleinopathies and related neurodegenerative diseases.

biophysics↗

bioRxiv2020

Machine learning models for predicting protein condensate formation from sequence determinants and embeddings

Intracellular phase separation of proteins into biomolecular condensates is increasingly recognised as an important phenomenon for cellular compartmentalisation and regulation of biological function. 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, here, we established an in silico strategy for understanding on a global level the associations between protein sequence and condensate formation, and used this information to construct machine learning classifiers for predicting liquid-liquid phase separation (LLPS) from protein sequence. Our analysis highlighted that LLPS-prone sequences are more disordered, hydrophobic and of lower Shannon entropy than sequences in the Protein Data Bank or the Swiss-Prot database, and have their disordered regions enriched in polar, aromatic and charged residues. Using these determining features together with neural network based word2vec sequence embeddings, we developed machine learning classifiers for predicting protein condensate formation. Our model, trained to distinguish LLPS-prone sequences from structured proteins, achieved high accuracy (93%; 25-fold cross-validation) and identified condensate forming sequences from external independent test data at 97% sensitivity. Moreover, in combination with a classifier that had developed a nuanced insight into the features governing protein phase behaviour by learning to distinguish between sequences of varying LLPS propensity, the sensitivity was supplemented with high specificity (approximated ROC-AUC of 0.85). These results provide a platform rooted in molecular principles for understanding protein phase behaviour. The predictor is accessible from https://deephase.ch.cam.ac.uk/. Significance StatementThe tendency of many cellular proteins to form protein-rich biomolecular condensates underlies the formation of subcellular compartments and has been linked to various physiological functions. Understanding the molecular basis of this fundamental process and predicting protein phase behaviour have therefore become important objectives. To develop a global understanding of how protein sequence determines its phase behaviour, here, we constructed bespoke datasets of proteins of varying phase separation propensity and identified explicit biophysical and sequence-specific features common to phase separating proteins. Moreover, by combining this insight with neural network based sequence embeddings, we trained machine learning classifiers that identified phase separating sequences with high accuracy, including from independent external test data. The predictor is available from https://deephase.ch.cam.ac.uk/.

biophysics↗

bioRxiv2020

Direct digital sensing of proteins through single-molecule optofluidics

The detection of proteins is of central importance to biomolecular analysis and diagnostics, yet fundamental limitations due to the surface-based nature of most sensing approaches persist, and limited improvements have been designed to integrate multimodal information beyond concentration measurements. Here we present a single-molecule microfluidic sensing platform for 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-concentrations 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. Together, DigitISA constitutes a new experimental paradigm for the digital sensing of protein biomarkers, and enables analyses of targets that would otherwise be hard or impossible to address by conventional immuno-sensing techniques.

biophysics↗

bioRxiv2020

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

Many cellular proteins demix spontaneously from solution to form liquid condensates. These phase-separated systems have wide-ranging roles in health and disease. Elucidating the molecular driving forces underlying liquid-liquid phase separation (LLPS) is therefore a key objective for understanding biological function and malfunction. Here we show that proteins implicated in cellular LLPS, including FUS, TDP-43, Brd4, Sox2, and Annexin A11, which form condensates at low salt concentrations, can reenter a phase-separated regime at high salt concentrations. By bringing together experiments and simulations, we demonstrate that phase separation 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 provides a new view on the cooperation of hydrophobicity and non-ionic interactions as non-specific driving forces for the condensation process, with important implications for aberrant function, druggability, and material properties of biomolecular condensates.

biophysics↗

bioRxiv2020

Single particle zeta-potential measurements reveal the role of electrostatics in protein condensate stability

Liquid-liquid phase separation underlies the formation of biological condensates. Physically, such systems are microemulsions which have a general propensity to fuse and coalesce; however, many condensates persist as independent droplets inside cells. This stability is crucial for their functioning, 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 modelling, we investigate how the forces that sustain condensates impact their stability against fusion. By comparing PR25:PolyU and FUS condensates, we show that a higher condensate surface charge correlates with a lower fusion propensity, and that this behavior can be inferred from their zeta potentials. We reveal that overall stabilization against fusion stems from a combination of repulsive forces between condensates and the effects that surface electrostatics have on lowering surface tension, thus shedding light on the molecular determinants of condensate coalescence.

biophysics↗

bioRxiv2020

Rapid Fractionation and Characterisation of Alpha-Synuclein Oligomers in Solution

Oligomeric intermediates are implicated as neurotoxins in the pathogenesis of protein mis-folding diseases. Structural, biophysical and biochemical characterisation of these species is challenging due to their heterogeneous and transient nature, and their typically low abun-dance. Here, we show that microfluidic free-flow electrophoresis is capable of separating heterogeneous oligomer mixtures on a timescale of seconds, at least two orders of magnitude faster than conventional techniques. This enables analysis of oligomer structural heterogeneity, zeta-potential and immunochemistry with minimal sample perturbation under physiologically-relevant conditions.

biophysics↗

bioRxiv2018

ATPase and protease domain movements in the bacterial AAA+ protease FtsH are driven by thermal fluctuations

AAA+ proteases are essential players in cellular pathways of protein degradation. Elucidating their conformational behavior is key for understanding their reaction mechanism and, importantly, for elaborating our understanding of mutation-induced protease deficiencies. Here, we study the structural dynamics of the Thermotoga maritima AAA+ hexameric ring metalloprotease FtsH (TmFtsH). Using a single-molecule Forster resonance energy transfer approach to monitor ATPase and protease inter-domain conformational changes in real time, we show that TmFtsH--even in the absence of nucleotide--is a highly dynamic protease undergoing conformational transitions between five states on the second timescale in a sequential manner. Addition of ATP does not influence the number of states nor change the timescale of domain motions, but affects the state occupancy distribution leading to an inter-domain compaction. These findings suggest that thermal energy, but not chemical energy, provides the major driving force for conformational switching, while ATP, through a state reequilibration, introduces directionality into this process. The TmFtsH A359V mutation, a homolog of the human pathogenic A510V mutation of paraplegin (SPG7) causing hereditary spastic paraplegia (HSP), does not affect the dynamic behavior of the protease but impairs the ATP-coupled domain compaction and, thus, may account for protease malfunctioning and pathogenesis in HSP.

molecular biology↗