Monitoring protein unfolding transitions by NMR-spectroscopy

The Prenucleation Equilibrium of the Parathyroid Hormone Determines the Critical Aggregation Concentration and Amyloid Fibril Nucleation

Nucleation and growth of amyloid fibrils were found to only occur in supersaturated solutions above a critical concentration (ccrit ). The biophysical meaning of ccrit remained mostly obscure, since typical low values of ccrit in the sub-μM range hamper investigations of potential oligomeric states and their structure. Here, we investigate the parathyroid hormone PTH84 as an example of a functional amyloid fibril forming peptide with a comparably high ccrit of 67±21 μM. We describe a complex concentration dependent prenucleation ensemble of oligomers of different sizes and secondary structure compositions and highlight the occurrence of a trimer and tetramer at ccrit as possible precursors for primary fibril nucleation. Furthermore, the soluble state found in equilibrium with fibrils adopts to the prenucleation state present at ccrit . Our study sheds light onto early events of amyloid formation directly related to the critical concentration and underlines oligomer formation as a key feature of fibril nucleation. Our results contribute to a deeper understanding of the determinants of supersaturated peptide solutions. In the current study we present a biophysical approach to investigate ccrit of amyloid fibril formation of PTH84 in terms of secondary structure, cluster size and residue resolved intermolecular interactions during oligomer formation. Throughout the investigated range of concentrations (1 μM to 500 μM) we found different states of oligomerization with varying ability to contribute to primary fibril nucleation and with a concentration dependent equilibrium. In this context, we identified the previously described ccrit of PTH84 to mark a minimum concentration for the formation of homo-trimers/tetramers. These investigations allowed us to characterize molecular interactions of various oligomeric states that are further converted into elongation competent fibril nuclei during the lag phase of a functional amyloid forming peptide.

Non-uniform sampling of similar NMR spectra and its application to studies of the interaction between alpha-synuclein and liposomes

The accelerated acquisition of multidimensional NMR spectra using sparse non-uniform sampling (NUS) has been widely adopted in recent years. The key concept in NUS is that a major part of the data is omitted during measurement, and then reconstructed using, for example, compressed sensing (CS) methods. CS requires spectra to be compressible, that is, they should contain relatively few "significant" points. The more compressible the spectrum, the fewer experimental NUS points needed in order for it to be accurately reconstructed. In this paper we show that the CS processing of similar spectra can be enhanced by reconstructing only the differences between them. Accurate reconstruction can be obtained at lower sampling levels as the difference is sparser than the spectrum itself. In many situations this method is superior to "conventional" compressed sensing. We exemplify the concept of "difference CS" with one such case-the study of alpha-synuclein binding to liposomes and its dependence on temperature. To obtain information on temperature-dependent transitions between different states, we need to acquire several dozen spectra at various temperatures, with and without the presence of liposomes. Our detailed investigation reveals that changes in the binding modes of the alpha-synuclein ensemble are not only temperature-dependent but also show non-linear behavior in their transitions. Our proposed CS processing approach dramatically reduces the number of NUS points required and thus significantly shortens the experimental time.

Protein Stability─Analysis of Heat and Cold Denaturation without and with Unfolding Models

Protein stability is important in many areas of life sciences. Thermal protein unfolding is investigated extensively with various spectroscopic techniques. The extraction of thermodynamic properties from these measurements requires the application of models. Differential scanning calorimetry (DSC) is less common, but is unique as it measures directly a thermodynamic property, that is, the heat capacity C_p(T). The analysis of C_p(T) is usually performed with the chemical equilibrium two-state model. This is not necessary and leads to incorrect thermodynamic consequences. Here we demonstrate a straightforward model-independent evaluation of heat capacity experiments in terms of protein unfolding enthalpy ΔH(T), entropy ΔS(T), and free energy ΔG(T)). This now allows the comparison of the experimental thermodynamic data with the predictions of different models. We critically examined the standard chemical equilibrium two-state model, which predicts a positive free energy for the native protein, and diverges distinctly from the experimental temperature profiles. We propose two new models which are equally applicable to spectroscopy and calorimetry. The Θ_U(T)-weighted chemical equilibrium model and the statistical-mechanical two-state model provide excellent fits of the experimental data. They predict sigmoidal temperature profiles for enthalpy and entropy, and a trapezoidal temperature profile for the free energy. This is illustrated with experimental examples for heat and cold denaturation of lysozyme and β-lactoglobulin. We then show that the free energy is not a good criterion to judge protein stability. More useful parameters are discussed, including protein cooperativity. The new parameters are embedded in a well-defined thermodynamic context and are amenable to molecular dynamics calculations.