Conformationally selective multidimensional chemical shift ranges in proteins from a PACSY database purged using intrinsic quality criteria

Charting the solid-state NMR signals of polysaccharides: A database-driven roadmap

Solid-state nuclear magnetic resonance (ssNMR) measurements of intact cell walls and cellular samples often generate spectra that are difficult to interpret due to the presence of many coexisting glycans and the structural polymorphism observed in native conditions. To overcome this analytical challenge, we present a statistical approach for analyzing carbohydrate signals using high-resolution ssNMR data indexed in a carbohydrate database. We generate simulated spectra to demonstrate the chemical shift dispersion and compare this with experimental data to facilitate the identification of important fungal and plant polysaccharides, such as chitin and glucans in fungi and cellulose, hemicellulose, and pectic polymers in plants. We also demonstrate that chemically distinct carbohydrates from different organisms may produce almost identical signals, highlighting the need for high-resolution spectra and validation of resonance assignments. Our study provides a means to differentiate the characteristic signals of major carbohydrates and allows us to summarize currently undetected polysaccharides in plants and fungi, which may inspire future investigations.

A solid beta-sheet structure is formed at the surface of FUS droplets during aging

Phase transitions are important to understand cell dynamics, and the maturation of liquid droplets is relevant to neurodegenerative disorders. We combined NMR and Raman spectroscopies with microscopy to follow, over a period of days to months, droplet maturation of the protein fused in sarcoma (FUS). Our study reveals that the surface of the droplets plays a critical role in this process, while RNA binding prevents it. The maturation kinetics are faster in an agarose-stabilized biphasic sample compared with a monophasic condensed sample, owing to the larger surface-to-volume ratio. In addition, Raman spectroscopy reports structural differences upon maturation between the inside and the surface of droplets, which is comprised of β-sheet content, as revealed by solid-state NMR. In agreement with these observations, a solid crust-like shell is observed at the surface using microaspiration. Ultimately, matured droplets were converted into fibrils involving the prion-like domain as well as the first RGG motif.

Distinguishing Different Hydrogen-Bonded Helices in Proteins by Efficient 1H-Detected Three-Dimensional Solid-State NMR

Helical structures in proteins include not only α-helices but also 310 and π helices. These secondary structures differ in the registry of the C═O···H-N hydrogen bonds, which are i to i + 4 for α-helices, i to i + 3 for 310 helices, and i to i + 5 for π-helices. The standard NMR observable of protein secondary structures are chemical shifts, which are, however, insensitive to the precise type of helices. Here, we introduce a three-dimensional (3D) 1H-detected experiment that measures and assigns CO-HN cross-peaks to distinguish the different types of hydrogen-bonded helices. This hCOhNH experiment combines efficient cross-polarization from CO to HN with 13C, 15N, and 1H chemical shift correlation to detect the relative proximities of the COi-Hi+jN spin pairs. We demonstrate this experiment on the membrane-bound transmembrane domain of the SARS-CoV-2 envelope (E) protein (ETM). We show that the C-terminal five residues of ETM form a 310-helix, whereas the rest of the transmembrane domain have COi-Hi+4N hydrogen bonds that are characteristic of α-helices. This result confirms the recent high-resolution solid-state NMR structure of the open state of ETM, which was solved in the absence of explicit hydrogen-bonding restraints. This C-terminal 310 helix may facilitate proton and calcium conduction across the hydrophobic gate of the channel. This hCOhNH experiment is generally applicable and can be used to distinguish not only different types of helices but also different types of β-strands and other hydrogen-bonded conformations in proteins.

Probing the Conformational Space of the Cannabinoid Receptor 2 and a Systematic Investigation of DNP-Enhanced MAS NMR Spectroscopy of Proteins in Detergent Micelles

Tremendous progress has been made in determining the structures of G-protein coupled receptors (GPCR) and their complexes in recent years. However, understanding activation and signaling in GPCRs is still challenging due to the role of protein dynamics in these processes. Here, we show how dynamic nuclear polarization (DNP)-enhanced magic angle spinning nuclear magnetic resonance in combination with a unique pair labeling approach can be used to study the conformational ensemble at specific sites of the cannabinoid receptor 2. To improve the signal-to-noise, we carefully optimized the DNP sample conditions and utilized the recently introduced AsymPol-POK as a polarizing agent. We could show qualitatively that the conformational space available to the protein backbone is different in different parts of the receptor and that a site in TM7 is sensitive to the nature of the ligand, whereas a site in ICL3 always showed large conformational freedom.

Characterization of conformational heterogeneity via higher-dimensionality, proton-detected solid-state NMR

Site-specific heterogeneity of solid protein samples can be exploited as valuable information to answer biological questions ranging from thermodynamic properties determining fibril formation to protein folding and conformational stability upon stress. In particular, for proteins of increasing molecular weight, however, site-resolved assessment without residue-specific labeling is challenging using established methodology, which tends to rely on carbon-detected 2D correlations. Here we develop purely chemical-shift-based approaches for assessment of relative conformational heterogeneity that allows identification of each residue via four chemical-shift dimensions. High dimensionality diminishes the probability of peak overlap in the presence of multiple, heterogeneously broadened resonances. Utilizing backbone dihedral-angle reconstruction from individual contributions to the peak shape either via suitably adapted prediction routines or direct association with a relational database, the methods may in future studies afford assessment of site-specific heterogeneity of proteins without site-specific labeling.

van der Wel P. Selective observation of semi-rigid non-core residues in dynamically complex mutant huntingtin protein fibrils

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Mutant huntingtin exon 1 fibrils feature a broad range of molecular dynamics.

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Molecular motion is coupled to water dynamics outside the fiber core.

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Dynamics-based spectral editing ssNMR reveals mobile non-core residues.

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Intermediate-motion selection via dipolar dephasing of rigid sites.

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Semi-mobile glutamines outside the fiber core observed and identified.

Many amyloid-forming proteins, which are normally intrinsically disordered, undergo a disorder-to-order transition to form fibrils with a rigid β-sheet core flanked by disordered domains. Solid-state NMR (ssNMR) and cryogenic electron microscopy (cryoEM) excel at resolving the rigid structures within amyloid cores but studying the dynamically disordered domains remains challenging. This challenge is exemplified by mutant huntingtin exon 1 (HttEx1), which self-assembles into pathogenic neuronal inclusions in Huntington disease (HD). The mutant protein’s expanded polyglutamine (polyQ) segment forms a fibril core that is rigid and sequestered from the solvent. Beyond the core, solvent-exposed surface residues mediate biological interactions and other properties of fibril polymorphs. Here we deploy magic angle spinning ssNMR experiments to probe for semi-rigid residues proximal to the fibril core and examine how solvent dynamics impact the fibrils’ segmental dynamics. Dynamic spectral editing (DYSE) 2D ssNMR based on a combination of cross-polarization (CP) ssNMR with selective dipolar dephasing reveals the weak signals of solvent-mobilized glutamine residues, while suppressing the normally strong background of rigid core signals. This type of ‘intermediate motion selection’ (IMS) experiment based on cross-polarization (CP) ssNMR, is complementary to INEPT- and CP-based measurements that highlight highly flexible or highly rigid protein segments, respectively. Integration of the IMS-DYSE element in standard CP-based ssNMR experiments permits the observation of semi-rigid residues in a variety of contexts, including in membrane proteins and protein complexes. We discuss the relevance of semi-rigid solvent-facing residues outside the fibril core to the latter’s detection with specific dyes and positron emission tomography tracers.

Mass data processing and multidimensional database management based on deep learning

With the rapid development of the Internet of Things, the requirements for massive data processing technology are getting higher and higher. Traditional computer data processing capabilities can no longer deliver fast, simple, and efficient data analysis and processing for today’s massive data processing due to the real-time, massive, polymorphic, and heterogeneous characteristics of Internet of Things data. Mass heterogeneous data of different types of subsystems in the Internet of Things need to be processed and stored uniformly, so the mass data processing method is required to be able to integrate multiple different networks, multiple data sources, and heterogeneous mass data and be able to perform processing on these data. Therefore, this article proposes massive data processing and multidimensional database management based on deep learning to meet the needs of contemporary society for massive data processing. This article has deeply studied the basic technical methods of massive data processing, including MapReduce technology, parallel data technology, database technology based on distributed memory databases, and distributed real-time database technology based on cloud computing technology, and constructed a massive data fusion algorithm based on deep learning. The model and the multidimensional online analytical processing model of the multidimensional database based on deep learning analyze the performance, scalability, load balancing, data query, and other aspects of the multidimensional database based on deep learning. It is concluded that the accuracy of multidimensional database query data is as high as 100%, and the accuracy of the average data query time is only 0.0053 s, which is much lower than the general database query time.

POKY software tools encapsulating assignment strategies for solution and solid-state protein NMR data

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New tools support efficient analysis of solution and solid-state NMR spectra of proteins.

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POKY integrates a powerful suite of software packages for automated assignments.

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The Versatile Assigner module validates assignments through probabilistic analysis.

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The operation of these tools is supported by on-line guidance.

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The performance of these tools is evaluated in reference to competing software.

NMR spectroscopy provides structural and functional information about biomolecules and their complexes. The complexity of these systems can make the NMR data difficult to interpret, particularly for newer users of NMR technology, who may have limited understanding of the tools available and how they are used. To alleviate this problem, we have created software based on standardized workflows for both solution and solid-state NMR spectroscopy of proteins. These tools assist with manual and automated peak picking and with chemical shift assignment and validation. They provide users with an optimized path through spectral analysis that can help them perform the necessary tasks more efficiently.

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

As the first potassium channel with an x-ray structure determined, and given its homology to eukaryotic channels, the pH-gated prokaryotic channel KcsA has been extensively studied. Nevertheless, questions related, in particular, to the allosteric coupling between its gates remain open. The many currently available x-ray crystallography structures appear to correspond to various stages of activation and inactivation, offering insights into the molecular basis of these mechanisms. Since these studies have required mutations, complexation with antibodies, and substitution of detergents in place of lipids, examining the channel under more native conditions is desirable. Solid-state nuclear magnetic resonance (SSNMR) can be used to study the wild-type protein under activating conditions (low pH), at room temperature, and in bacteriomimetic liposomes. In this work, we sought to structurally assign the activated state present in SSNMR experiments. We used a combination of molecular dynamics (MD) simulations, chemical shift prediction algorithms, and Bayesian inference techniques to determine which of the most plausible x-ray structures resolved to date best represents the activated state captured in SSNMR. We first identified specific nuclei with simulated NMR chemical shifts that differed significantly when comparing partially open vs fully open ensembles from MD simulations. The simulated NMR chemical shifts for those specific nuclei were then compared to experimental ones, revealing that the simulation of the partially open state was in good agreement with the SSNMR data. Nuclei that discriminate effectively between partially and fully open states belong to residues spread over the sequence and provide a molecular level description of the conformational change.

Hydration-Induced Structural Transitions in Biomimetic Tandem Repeat Proteins

A major challenge in developing biomimetic, high-performance, and sustainable products is the accurate replication of the biological materials' striking properties, such as high strength, self-repair, and stimuli-responsiveness. The rationalization of such features on the microscopic scale, together with the rational design of synthetic materials, is currently hindered by our limited understanding of the sequence-structure-property relationship. Here, employing state-of-the-art nuclear magnetic resonance (NMR) spectroscopy, we link the atomistic structural and dynamic properties of an artificial bioinspired tandem repeat protein TR(1,11) to its stunning macroscopic properties including high elasticity, self-healing capabilities, and record-holding proton conductivity among biological materials. We show that the hydration-induced structural rearrangement of the amorphous Gly-rich soft segment and the ordered Ala-rich hard segment is the key to the material's outstanding physical properties. We found that in the hydrated state both the Ala-rich ordered and Gly-rich disordered parts contribute to the formation of the nanoconfined β-sheets, thereby enhancing the strength and toughness of the material. This restructuring is accompanied by fast proline ring puckering and backbone cis-trans isomerization at the water-protein interface, which in turn enhances the elasticity and the thermal conductivity of the hydrated films. Our in-depth characterization provides a solid ground for the development of next-generation materials with improved properties.

Regulatory inter-domain interactions influence Hsp70 recruitment to the DnaJB8 chaperone

The Hsp40/Hsp70 chaperone families combine versatile folding capacity with high substrate specificity, which is mainly facilitated by Hsp40s. The structure and function of many Hsp40s remain poorly understood, particularly oligomeric Hsp40s that suppress protein aggregation. Here, we used a combination of biochemical and structural approaches to shed light on the domain interactions of the Hsp40 DnaJB8, and how they may influence recruitment of partner Hsp70s. We identify an interaction between the J-Domain (JD) and C-terminal domain (CTD) of DnaJB8 that sequesters the JD surface, preventing Hsp70 interaction. We propose a model for DnaJB8-Hsp70 recruitment, whereby the JD-CTD interaction of DnaJB8 acts as a reversible switch that can control the binding of Hsp70. These findings suggest that the evolutionarily conserved CTD of DnaJB8 is a regulatory element of chaperone activity in the proteostasis network.

Solid-state NMR spectroscopy

Solid-state nuclear magnetic resonance (NMR) spectroscopy is an atomic-level method used to determine the chemical structure, three-dimensional structure, and dynamics of solids and semi-solids. This Primer summarizes the basic principles of NMR as applied to the wide range of solid systems. The fundamental nuclear spin interactions and the effects of magnetic fields and radiofrequency pulses on nuclear spins are the same as in liquid-state NMR. However, because of the anisotropy of the interactions in the solid state, the majority of high-resolution solid-state NMR spectra is measured under magic-angle spinning (MAS), which has profound effects on the types of radiofrequency pulse sequences required to extract structural and dynamical information. We describe the most common MAS NMR experiments and data analysis approaches for investigating biological macromolecules, organic materials, and inorganic solids. Continuing development of sensitivity-enhancement approaches, including 1H-detected fast MAS experiments, dynamic nuclear polarization, and experiments tailored to ultrahigh magnetic fields, is described. We highlight recent applications of solid-state NMR to biological and materials chemistry. The Primer ends with a discussion of current limitations of NMR to study solids, and points to future avenues of development to further enhance the capabilities of this sophisticated spectroscopy for new applications.

Micellar TIA1 with folded RNA binding domains as a model for reversible stress granule formation

TIA1, a protein critical for eukaryotic stress response and stress granule formation, is structurally characterized in full-length form. TIA1 contains three RNA recognition motifs (RRMs) and a C-terminal low-complexity domain, sometimes referred to as a "prion-related domain" or associated with amyloid formation. Under mild conditions, full-length (fl) mouse TIA1 spontaneously oligomerizes to form a metastable colloid-like suspension. RRM2 and RRM3, known to be critical for function, are folded similarly in excised domains and this oligomeric form of apo fl TIA1, based on NMR chemical shifts. By contrast, the termini were not detected by NMR and are unlikely to be amyloid-like. We were able to assign the NMR shifts with the aid of previously assigned solution-state shifts for the RRM2,3 isolated domains and homology modeling. We present a micellar model of fl TIA1 wherein RRM2 and RRM3 are colocalized, ordered, hydrated, and available for nucleotide binding. At the same time, the termini are disordered and phase separated, reminiscent of stress granule substructure or nanoscale liquid droplets.

Selective One-Dimensional 13C-13C Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers Including Plant Cell Walls, Peptides, and Spider Silk

Two-dimensional (2D) and 3D through-space ¹³C-¹³C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from ¹³C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D ¹³C-¹³C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D ¹³C-¹³C spin-diffusion methods described here apply in select cases in which the 1D ¹³C solid-state NMR spectrum displays chemical shift-resolved moieties. This is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D ¹³C-¹³C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of ¹³C-¹³C spin-diffusion buildup curves and extraction of spin-diffusion time constants T_SD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to ¹³C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ∼0.45-0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks.

Increased Dynamics of α-Synuclein Fibrils by β-Synuclein Leads to Reduced Seeding and Cytotoxicity

Alpha-synuclein (αS) fibrils are toxic to cells and contribute to the pathogenesis and progression of Parkinson's disease and other synucleinopathies. β-Synuclein (βS), which co-localizes with αS, has been shown to provide a neuroprotective effect, but the molecular mechanism by which this occurs remains elusive. Here we show that αS fibrils formed in the presence of βS are less cytotoxic, exhibit reduced cell seeding capacity and are more resistant to fibril shedding compared to αS fibrils alone. Using solid-state NMR, we found that the overall structure of the core of αS fibrils when co-incubated with βS is minimally perturbed, however, the dynamics of Lys and Thr residues, located primarily in the imperfect KTKEGV repeats of the αS N-terminus, are increased. Our results suggest that amyloid fibril dynamics may play a key role in modulating toxicity and seeding. Thus, enhancing the dynamics of amyloid fibrils may be a strategy for future therapeutic targeting of neurodegenerative diseases.

Automatic 13C chemical shift reference correction for unassigned protein NMR spectra

Poor chemical shift referencing, especially for ¹³C in protein Nuclear Magnetic Resonance (NMR) experiments, fundamentally limits and even prevents effective study of biomacromolecules via NMR, including protein structure determination and analysis of protein dynamics. To solve this problem, we constructed a Bayesian probabilistic framework that circumvents the limitations of previous reference correction methods that required protein resonance assignment and/or three-dimensional protein structure. Our algorithm named Bayesian Model Optimized Reference Correction (BaMORC) can detect and correct ¹³C chemical shift referencing errors before the protein resonance assignment step of analysis and without three-dimensional structure. By combining the BaMORC methodology with a new intra-peaklist grouping algorithm, we created a combined method called Unassigned BaMORC that utilizes only unassigned experimental peak lists and the amino acid sequence. Unassigned BaMORC kept all experimental three-dimensional HN(CO)CACB-type peak lists tested within ± 0.4 ppm of the correct ¹³C reference value. On a much larger unassigned chemical shift test set, the base method kept ¹³C chemical shift referencing errors to within ± 0.45 ppm at a 90% confidence interval. With chemical shift assignments, Assigned BaMORC can detect and correct ¹³C chemical shift referencing errors to within ± 0.22 at a 90% confidence interval. Therefore, Unassigned BaMORC can correct ¹³C chemical shift referencing errors when it will have the most impact, right before protein resonance assignment and other downstream analyses are started. After assignment, chemical shift reference correction can be further refined with Assigned BaMORC. These new methods will allow non-NMR experts to detect and correct ¹³C referencing error at critical early data analysis steps, lowering the bar of NMR expertise required for effective protein NMR analysis.

Methionine oxidized apolipoprotein A-I at the crossroads of HDL biogenesis and amyloid formation

Apolipoprotein A-I (apoA-I) shares with other exchangeable apolipoproteins a high level of structural plasticity. In the lipid-free state, the apolipoprotein amphipathic α-helices interact intra- and intermolecularly, providing structural stabilization by self-association. We have reported that lipid-free apoA-I becomes amyloidogenic upon physiologically relevant (myeloperoxidase-mediated) Met oxidation. In this study, we established that Met oxidation promotes amyloidogenesis by reducing the stability of apoA-I monomers and irreversibly disrupting self-association. The oxidized apoA-I monomers also exhibited increased cellular cholesterol release capacity and stronger association with macrophages, compared to nonoxidized apoA-I. Of physiologic relevance, preformed oxidized apoA-I amyloid fibrils induced amyloid formation in nonoxidized apoA-I. This process was enhanced when self-association of nonoxidized apoA-I was disrupted by thermal treatment. Solid state NMR analysis revealed that aggregates formed by seeded nonoxidized apoA-I were structurally similar to those formed by the oxidized protein, featuring a β-structure-rich amyloid fold alongside α-helices retained from the native state. In atherosclerotic lesions, the conditions that promote apoA-I amyloid formation are readily available: myeloperoxidase, active oxygen species, low pH, and high concentration of lipid-free apoA-I. Our results suggest that even partial Met oxidation of apoA-I can nucleate amyloidogenesis, thus sequestering and inactivating otherwise antiatherogenic and HDL-forming apoA-I.-Witkowski, A., Chan, G. K. L., Boatz, J. C., Li, N. J., Inoue, A. P., Wong, J. C., van der Wel, P. C. A., Cavigiolio, G. Methionine oxidized apolipoprotein A-I at the crossroads of HDL biogenesis and amyloid formation.