Protein structure determination in human cells by in-cell NMR and a reporter system to optimize protein delivery or transexpression

Cellular Applications of DNP Solid-State NMR - State of the Art and a Look to the Future

Sensitivity enhanced dynamic nuclear polarization solid-state NMR is emerging as a powerful technique for probing the structural properties of conformationally homogenous and heterogenous biomolecular species irrespective of size at atomic resolution within their native environments. Herein we detail advancements that have made acquiring such data, specifically within the confines of intact bacterial and eukaryotic cell a reality and further discuss the type of structural information that can presently be garnered by the technique's exploitation. Subsequently, we discuss bottlenecks that have thus far curbed cellular DNP-ssNMR's broader adoption namely due a lack of sensitivity and spectral resolution. We also explore possible solutions ranging from utilization of new pulse sequences, design of better performing polarizing agents, and application of additional biochemical/ cell biological methodologies.

Identifying the minimal sets of distance restraints for FRET-assisted protein structural modeling

Proteins naturally occur in crowded cellular environments and interact with other proteins, nucleic acids, and organelles. Since most previous experimental protein structure determination techniques require that proteins occur in idealized, non-physiological environments, the effects of realistic cellular environments on protein structure are largely unexplored. Recently, Förster resonance energy transfer (FRET) has been shown to be an effective experimental method for investigating protein structure in vivo. Inter-residue distances measured in vivo can be incorporated as restraints in molecular dynamics (MD) simulations to model protein structural dynamics in vivo. Since most FRET studies only obtain inter-residue separations for a small number of amino acid pairs, it is important to determine the minimum number of restraints in the MD simulations that are required to achieve a given root-mean-square deviation (RMSD) from the experimental structural ensemble. Further, what is the optimal method for selecting these inter-residue restraints? Here, we implement several methods for selecting the most important FRET pairs and determine the number of pairs N r that are needed to induce conformational changes in proteins between two experimentally determined structures. We find that enforcing only a small fraction of restraints, N r / N ≲ 0.08 , where N is the number of amino acids, can induce the conformational changes. These results establish the efficacy of FRET-assisted MD simulations for atomic scale structural modeling of proteins in vivo.

Significance

Determining protein structure in vivo is essential for understanding protein function. Most protein structures have been studied in non-physiological conditions using x-ray crystallography, NMR spectroscopy, and cryo-electron microscopy. Thus, we do not know whether the cellular environment significantly affects protein structure. We emphasize the benefits of FRET-assisted molecular dynamics simulations in characterizing protein structure in vivo at the atomic scale. We identify the minimum number of FRET pairs that can induce conformational changes in several proteins, including one that has been characterized using in-cell NMR.

Background signal suppression by opposite polarity subtraction for targeted DNP NMR spectroscopy on mixture samples

A novel method for background signal suppression is introduced to improve the selectivity of dynamic nuclear polarization (DNP) NMR spectroscopy in the study of target molecules within complex mixtures. The method uses subtraction between positively and negatively enhanced DNP spectra, leading to an improved contrast factor, which is the ratio between the target and background signal intensities. The proposed approach was experimentally validated using a reverse-micelle system that confines the target molecules together with the polarizing agent, OX063 trityl. A substantial increase in the contrast factor was observed, and the contrast factor was optimized through careful selection of the DNP build-up time. A simulation study based on the experimental results provides insights into a strategy for choosing the appropriate DNP build-up time and the corresponding selectivity of the method. Further analysis revealed a broad applicability of the technique, encompassing studies from large biomolecules to surface-modified polymers, depending on the nuclear spin diffusion rate with a range of gyromagnetic ratios.

Cell-to-cell transmitted alpha-synuclein recapitulates experimental Parkinson's disease

Parkinson's disease is characterized by a progressive accumulation of alpha-Synuclein (αSyn) neuronal inclusions called Lewy bodies in the nervous system. Lewy bodies can arise from the cell-to-cell propagation of αSyn, which can occur via sequential steps of secretion and uptake. Here, by fusing a removable short signal peptide to the N-terminus of αSyn, we developed a novel mouse model with enhanced αSyn secretion and cell-to-cell transmission. Expression of the secreted αSyn in the mouse brain was under the control of a novel hybrid promoter in combination with adeno-associated virus serotype 9 (AAV9). This combination of promoter and viral vector induced a robust expression in neurons but not in the glia of injected mice. Biochemical characterization of the secreted αSyn revealed that, in cultured cells, this protein is released to the extracellular milieu via conventional secretion. The released αSyn is then internalized and processed by acceptor cells via the endosome-lysosome pathway indicating that the secreted αSyn is cell-to-cell transmitted. The secreted αSyn is aggregation-prone and amyloidogenic, and when expressed in the brain of wild-type non-transgenic mice, it induces a Parkinson's disease-like phenotype that includes a robust αSyn pathology in the substantia nigra, neuronal loss, neuroinflammation, and motor deficits, all the key features of experimental animal models of Parkinson's disease. In summary, a novel animal model of Parkinson's disease based on enhanced cell-to-cell transmission of αSyn was developed. The neuron-produced cell-to-cell transmitted αSyn triggers all phenotypic features of experimental Parkinson's disease in mice.

Multi-Dimensional Structure and Dynamics Landscape of Proteins in Mammalian Cells Revealed by In-Cell NMR

Governing function, half-life and subcellular localization, the 3D structure and dynamics of proteins are in nature constantly changing in a tightly regulated manner to fulfill the physiological and adaptive requirements of the cells. To find evidence for this hypothesis, we applied in-cell NMR to three folded model proteins and propose that the splitting of cross peaks constitutes an atomic fingerprint of distinct structural states that arise from multiple target binding co-existing inside mammalian cells. These structural states change upon protein loss of function or subcellular localisation into distinct cell compartments. In addition to peak splitting, we observed NMR signal intensity attenuations indicative of transient interactions with other molecules and dynamics on the microsecond to millisecond time scale.

Protein dynamics: The future is bright and complicated!

Biological life depends on motion, and this manifests itself in proteins that display motion over a formidable range of time scales spanning from femtoseconds vibrations of atoms at enzymatic transition states, all the way to slow domain motions occurring on micro to milliseconds. An outstanding challenge in contemporary biophysics and structural biology is a quantitative understanding of the linkages among protein structure, dynamics, and function. These linkages are becoming increasingly explorable due to conceptual and methodological advances. In this Perspective article, we will point toward future directions of the field of protein dynamics with an emphasis on enzymes. Research questions in the field are becoming increasingly complex such as the mechanistic understanding of high-order interaction networks in allosteric signal propagation through a protein matrix, or the connection between local and collective motions. In analogy to the solution to the "protein folding problem," we argue that the way forward to understanding these and other important questions lies in the successful integration of experiment and computation, while utilizing the present rapid expansion of sequence and structure space. Looking forward, the future is bright, and we are in a period where we are on the doorstep to, at least in part, comprehend the importance of dynamics for biological function.