Advanced database mining integrating sequence and structure bioinformatics with microfluidics challenges enzyme engineering

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Exploration of Protein Unfolding by Modelling Calorimetry Data from Reheating

Abstract Studies of protein unfolding mechanisms are critical for understanding protein functions inside cells, de novo protein design as well as defining the role of protein misfolding in neurodegenerative disorders. Calorimetry has proven indispensable in this regard for recording full energetic profiles of protein unfolding and permitting data fitting based on unfolding pathway models. While both kinetic and thermodynamic protein stability are analysed by varying scan rates and reheating, the latter is rarely used in curve-fitting, leading to a significant loss of information from experiments. To extract this information, we propose fitting both first and second scans simultaneously. Four most common single-peak transition models are considered: (i) fully reversible, (ii) fully irreversible, (iii) partially reversible transitions, and (iv) general three-state models. The method is validated using calorimetry data for chicken egg lysozyme, mutated Protein A, three wild-types of haloalkane dehalogenases, and a mutant stabilized by protein engineering. We show that modelling of reheating increases the precision of determination of unfolding mechanisms, free energies, temperatures, and heat capacity differences. Moreover, this modelling indicates whether alternative refolding pathways might occur upon cooling. The Matlab-based data fitting software tool and its user guide are provided as a supplement

The secondary nucleation of alpha-synuclein amyloid fibrils is suppressed under fully quiescent conditions

Seed amplification assays (SAAs) are a promising avenue for the early diagnosis of neurodegenerative diseases However, when amplifying fibrils from patient-derived samples in the commonly used format of multiwell plates, it is currently highly challenging to accurately quantify the aggregates. It is therefore desirable to transfer such assays into a digital format in microemulsion droplets to enable direct quantification of aggregate numbers. To achieve transfer from conventional plate-based to the microfluidic digital format, effective seed amplification needs to be achieved inside the microdroplets. It has been shown previously that alpha-synuclein fibril amplification is strongly promoted by acidic pH. Here, we establish a new set of assay conditions that enable highly efficient seed amplification in plates without any shaking. However, the same set of conditions displayed a very different behavior upon transfer to a microfluidic platform where no amplification was observed. We demonstrate that this is caused by the suppression of all secondary processes that could amplify the seeds in the complete absence of mechanical perturbations inside the microdroplets. We further show that the amplification inside droplets can be achieved by subjecting the microemulsions to high-frequency vibrations using a piezo device. Taken together, our results provide novel insights into the physical requirements of alpha-synuclein seed amplification and demonstrate a pathway towards the development of effective digital seed amplification assays

Droplet-Based Microfluidic Temperature-Jump Platform for the Rapid Assessment of Biomolecular Kinetics

Protein folding, unfolding, and aggregation are important in a variety of biological processes and intimately linked to “protein misfolding diseases”. The ability to perform experiments at different temperatures allows the extraction of important information regarding the kinetics and thermodynamics of such processes. Unfortunately, conventional stopped-flow methods are difficult to implement, generate limited information, and involve complex sample handling. To address this issue, we present a temperature-controlled droplet-based microfluidic platform that allows measurement of reaction kinetics on millisecond to second timescales and at temperatures between ambient and 90 °C. The utility of the microfluidic platform for measuring fast biomolecular kinetics at high temperatures is showcased through the investigation of the unfolding kinetics of haloalkane dehalogenases and the elongation of fibrils composed of the amyloid β peptide associated with Alzheimer’s disease. In addition, a deep-ultraviolet (UV) fluorescence microscope was developed for the on-chip recording of protein intrinsic fluorescence spectrum originating from aromatic amino acid residues. We envision that the developed optofluidic platform will find wide applicability in the analysis of biological processes, such as protein refolding and phase separation.ISSN:1520-6882ISSN:0003-270

Thermodynamic characterization of amyloid polymorphism by microfluidic transient incomplete separation

Amyloid fibrils of proteins such as α-synuclein are a hallmark of neurodegenerative diseases and much research has focused on their kinetics and mechanisms of formation. The question as to the thermodynamic stability of such structures has received much less attention. Here, we newly utilize the principle of transient incomplete separation of species in laminar flow in combination with chemical depolymerization for the quantification of amyloid fibril stability. The relative concentrations of fibrils and monomer at equilibrium are determined through an in situ separation of these species based on their different diffusivity inside a microfluidic capillary. The method is highly sample economical, using much less than a microliter of sample per data point and its only requirement is the presence of aromatic residues (W, Y) because of its label-free nature, which makes it widely applicable. Using this method, we investigate the differences in thermodynamic stability between different fibril polymorphs of α-synuclein and quantify these differences for the first time. Importantly, we show that fibril formation can be under kinetic or thermodynamic control and that a change in solution conditions can both stabilise and destabilise amyloid fibrils. Taken together, our results establish the thermodynamic stability as a well-defined and key parameter that can contribute towards a better understanding of the physiological roles of amyloid fibril polymorphism

Thermodynamic characterization of amyloid polymorphism by Taylor dispersion analysis

Amyloid fibrils of proteins such as α-synuclein are a hallmark of neurodegenerative diseases and much research has focused on their kinetics and mechanisms of formation. The question as to the thermodynamic stability of such structures has received much less attention. Here, we present a novel experimental method to quantify amyloid fibril stability based on chemical depolymerisation and Taylor dispersion analysis. The relative concentrations of fibrils and monomer at equilibrium are determined through an in situ separation of these species through Taylor dispersion in laminar flow inside a microfluidic capillary. This method is highly sample economical, using much less than a microliter of sample per data point and its only requirement is the presence of aromatic residues because of its label-free nature. Using this method, we investigate the differences in thermodynamic stability between different fibril polymorphs of α-synuclein and quantify these differences for the first time. Importantly, we show that fibril formation can be under kinetic or thermodynamic control and that a change in solution conditions can both stabilise and destabilise amyloid fibrils. Taken together, our results establish the thermodynamic stability as a well-defined and key parameter that can contribute towards a better understanding of the physiological roles of amyloid fibril polymorphism

Evolutionary analysis as a powerful complement to energy calculations for protein stabilization

Stability is one of the most important characteristics of proteins employed as biocatalysts, biotherapeutics, and biomaterials, and the role of computational approaches in modifying protein stability is rapidly expanding. We have recently identified stabilizing mutations in haloalkane dehalogenase DhaA using phylogenetic analysis but were not able to reproduce the effects of these mutations using force-field calculations. Here we tested four different hypotheses to explain the molecular basis of stabilization using structural, biochemical, biophysical, and computational analyses. We demonstrate that stabilization of DhaA by the mutations identified using the phylogenetic analysis is driven by both entropy and enthalpy contributions, in contrast to primarily enthalpy-driven stabilization by mutations designed by the force-field Comprehensive bioinformatics analysis revealed that more than half (53%) of 1 099 evolution-based stabilizing mutations would be evaluated as destabilizing by force-field calculations. Thermodynamic integration considers both folded and unfolded states and can describe the entropic component of stabilization, yet it is not suitable for predictive purposes due to its high computational demands. Altogether, our results strongly suggest that energetic calculations should be complemented by a phylogenetic analysis in protein-stabilization endeavors

Computational Protein Stabilization Can Affect Folding Energy Landscapes and Lead to Domain-Swapped Dimers

The functionality of a protein depends on its unique three-dimensional structure, which is a result of the folding process when the nascent polypeptide follows a funnel-like energy landscape to reach a global energy minimum. Computer-encoded algorithms are increasingly employed to stabilize native proteins for use in research and biotechnology applications. Here, we reveal a unique example where the computational stabilization of a monomeric α/β-hydrolase enzyme (Tm = 73.5°C; ΔTm > 23°C) affected the protein folding energy landscape. Introduction of eleven single-point stabilizing mutations based on force field calculations and evolutionary analysis yielded catalytically active domain-swapped intermediates trapped in local energy minima. Crystallographic structures revealed that these stabilizing mutations target cryptic hinge regions and newly introduced secondary interfaces, where they make extensive non-covalent interactions between the intertwined misfolded protomers. The existence of domain-swapped dimers in a solution is further confirmed experimentally by data obtained from SAXS and crosslinking mass spectrometry. Unfolding experiments showed that the domain-swapped dimers can be irreversibly converted into native-like monomers, suggesting that the domain-swapping occurs exclusively in vivo. Our findings uncovered hidden protein-folding consequences of computational protein design, which need to be taken into account when applying a rational stabilization to proteins of biological and pharmaceutical interest.</p

Advanced Database Mining of Efficient Biocatalysts by Sequence and Structure Bioinformatics and Microfluidics

Next-generation sequencing doubles genomic databases every 2.5 years. The accumulation of sequence data provides a unique opportunity to identify interesting biocatalysts directly in the databases without tedious and time-consuming engineering. Herein, we present a pipeline integrating sequence and structural bioinformatics with microfluidic enzymology for bioprospecting of efficient and robust haloalkane dehalogenases. The bioinformatic part identified 2,905 putative dehalogenases and prioritized a “small-but-smart” set of 45 genes, yielding 40 active enzymes, 24 of which were biochemically characterized by microfluidic enzymology techniques. Combining microfluidics with modern global data analysis provided precious mechanistic insights related to the high catalytic efficiency of selected enzymes. Overall, we have doubled the dehalogenation “toolbox” characterized over three decades, yielding biocatalysts that surpass the efficiency of currently available wild-type and engineered enzymes. This pipeline is generally applicable to other enzyme families and can accelerate the identification of efficient biocatalysts for industrial use