Multidimensional Dynamics of the Proteome in the Neurodegenerative and Aging Mammalian Brain.

The amount of any given protein in the brain is determined by the rates of its synthesis and destruction, which are regulated by different cellular mechanisms. Here, we combine metabolic labeling in live mice with global proteomic profiling to simultaneously quantify both the flux and amount of proteins in mouse models of neurodegeneration. In multiple models, protein turnover increases were associated with increasing pathology. This method distinguishes changes in protein expression mediated by synthesis from those mediated by degradation. In the AppNL-F knockin mouse model of Alzheimer's disease, increased turnover resulted from imbalances in both synthesis and degradation, converging on proteins associated with synaptic vesicle recycling (Dnm1, Cltc, Rims1) and mitochondria (Fis1, Ndufv1). In contrast to disease models, aging in wild-type mice caused a widespread decrease in protein recycling associated with a decrease in autophagic flux. Overall, this simple multidimensional approach enables a comprehensive mapping of proteome dynamics and identifies affected proteins in mouse models of disease and other live animal test settings.

High-Resolution Hydrogen-Deuterium Protection Factors from Sparse Mass Spectrometry Data Validated by Nuclear Magnetic Resonance Measurements.

Experimental measurement of time-dependent spontaneous exchange of amide protons with deuterium of the solvent provides information on the structure and dynamical structural variation in proteins. Two experimental techniques are used to probe the exchange: NMR, which relies on different magnetic properties of hydrogen and deuterium, and MS, which exploits the change in mass due to deuteration. NMR provides residue-specific information, that is, the rate of exchange or, analogously, the protection factor (i.e., the unitless ratio between the rate of exchange for a completely unstructured state and the observed rate). MS provides information that is specific to peptides obtained by proteolytic digestion. The spatial resolution of HDX-MS measurements depends on the proteolytic pattern of the protein, the fragmentation method used, and the overlap between peptides. Different computational approaches have been proposed to extract residue-specific information from peptide-level HDX-MS measurements. Here, we demonstrate the advantages of a method recently proposed that exploits self-consistency and classifies the possible sets of protection factors into a finite number of alternative solutions compatible with experimental data. The degeneracy of the solutions can be reduced (or completely removed) by exploiting the additional information encoded in the shape of the isotopic envelopes. We show how sparse and noisy MS data can provide high-resolution protection factors that correlate with NMR measurements probing the same protein under the same conditions.

Protein mechanics probed using simple molecular models.

BACKGROUND: Single-molecule experimental techniques such as optical tweezers or atomic force microscopy are a direct probe of the mechanical unfolding/folding of individual proteins. They are also a means to investigate free energy landscapes. Protein force spectroscopy alone provides limited information; theoretical models relate measurements to thermodynamic and kinetic properties of the protein, but do not reveal atomic level information. By building a molecular model of the protein and probing its properties through numerical simulation, one can gauge the response to an external force for individual interatomic interactions and determine structures along the unfolding pathway. In combination, single-molecule force probes and molecular simulations contribute to uncover the rich behavior of proteins when subjected to mechanical force. SCOPE OF REVIEW: We focus on how simplified protein models have been instrumental in showing how general properties of the free energy landscape of a protein relate to its response to mechanical perturbations. We discuss the role of simple protein models to explore the complexity of free energy landscapes and highlight important conceptual issues that more chemically accurate models with all-atom representations of proteins and solvent cannot easily address. MAJOR CONCLUSIONS: Native-centric, coarse-grained models, despite simplifications in chemical detail compared to all-atom models, can reproduce and interpret experimental results. They also highlight instances where the theoretical framework used to interpret single-molecule data is too simple. However, these simple models are not able to reproduce experimental findings where non-native contacts are involved. GENERAL SIGNIFICANCE: Mechanical forces are ubiquitous in the cell and it is increasingly clear that the way a protein responds to mechanical perturbation is important.