Benjamin Bardiaux

ARIA2: Automated NOE assignment and data integration in NMR structure calculation

UNLABELLEDnModern structural genomics projects demand for integrated methods for the interpretation and storage of nuclear magnetic resonance (NMR) data. Here we present version 2.1 of our program ARIA (Ambiguous Restraints for Iterative Assignment) for automated assignment of nuclear Overhauser enhancement (NOE) data and NMR structure calculation. We report on recent developments, most notably a graphical user interface, and the incorporation of the object-oriented data model of the Collaborative Computing Project for NMR (CCPN). The CCPN data model defines a storage model for NMR data, which greatly facilitates the transfer of data between different NMR software packages.nnnAVAILABILITYnA distribution with the source code of ARIA 2.1 is freely available at http://www.pasteur.fr/recherche/unites/Binfs/aria2.

Solid-state NMR and SAXS studies provide a structural basis for the activation of αB-crystallin oligomers

The small heat shock protein αB-crystallin (αB) contributes to cellular protection against stress. For decades, high-resolution structural studies on oligomeric αB have been confounded by its polydisperse nature. Here, we present a structural basis of oligomer assembly and activation of the chaperone using solid-state NMR and small-angle X-ray scattering (SAXS). The basic building block is a curved dimer, with an angle of ∼121° between the planes of the β-sandwich formed by α-crystallin domains. The highly conserved IXI motif covers a substrate binding site at pH 7.5. We observe a pH-dependent modulation of the interaction of the IXI motif with β4 and β8, consistent with a pH-dependent regulation of the chaperone function. N-terminal region residues Ser59-Trp60-Phe61 are involved in intermolecular interaction with β3. Intermolecular restraints from NMR and volumetric restraints from SAXS were combined to calculate a model of a 24-subunit αB oligomer with tetrahedral symmetry.

N-terminal domain of αB-crystallin provides a conformational switch for multimerization and structural heterogeneity

The small heat shock protein (sHSP) αB-crystallin (αB) plays a key role in the cellular protection system against stress. For decades, high-resolution structural studies on heterogeneous sHSPs have been confounded by the polydisperse nature of αB oligomers. We present an atomic-level model of full-length αB as a symmetric 24-subunit multimer based on solid-state NMR, small-angle X-ray scattering (SAXS), and EM data. The model builds on our recently reported structure of the homodimeric α-crystallin domain (ACD) and C-terminal IXI motif in the context of the multimer. A hierarchy of interactions contributes to build multimers of varying sizes: Interactions between two ACDs define a dimer, three dimers connected by their C-terminal regions define a hexameric unit, and variable interactions involving the N-terminal region define higher-order multimers. Within a multimer, N-terminal regions exist in multiple environments, contributing to the heterogeneity observed by NMR. Analysis of SAXS data allows determination of a heterogeneity parameter for this type of system. A mechanism of multimerization into higher-order asymmetric oligomers via the addition of up to six dimeric units to a 24-mer is proposed. The proposed asymmetric multimers explain the homogeneous appearance of αB in negative-stain EM images and the known dynamic exchange of αB subunits. The model of αB provides a structural basis for understanding known disease-associated missense mutations and makes predictions concerning substrate binding and the reported fibrilogenesis of αB.

3D Structure Determination of the Crh Protein from Highly Ambiguous Solid-State NMR Restraints

In a wide variety of proteins, insolubility presents a challenge to structural biology, as X-ray crystallography and liquid-state NMR are unsuitable. Indeed, no general approach is available as of today for studying the three-dimensional structures of membrane proteins and protein fibrils. We here demonstrate, at the example of the microcrystalline model protein Crh, how high-resolution 3D structures can be derived from magic-angle spinning solid-state NMR distance restraints for fully labeled protein samples. First, we show that proton-mediated rare-spin correlation spectra, as well as carbon-13 spin diffusion experiments, provide enough short, medium, and long-range structural restraints to obtain high-resolution structures of this 2 x 10.4 kDa dimeric protein. Nevertheless, the large number of 13C/15N spins present in this protein, combined with solid-state NMR line widths of about 0.5-1 ppm, induces substantial ambiguities in resonance assignments, preventing 3D structure determination by using distance restraints uniquely assigned on the basis of their chemical shifts. In the second part, we thus demonstrate that an automated iterative assignment algorithm implemented in a dedicated solid-state NMR version of the program ARIA permits to resolve the majority of ambiguities and to calculate a de novo 3D structure from highly ambiguous solid-state NMR data, using a unique fully labeled protein sample. We present, using distance restraints obtained through the iterative assignment process, as well as dihedral angle restraints predicted from chemical shifts, the 3D structure of the fully labeled Crh dimer refined at a root-mean-square deviation of 1.33 A.

Membrane-protein structure determination by solid-state NMR spectroscopy of microcrystals

Membrane proteins are largely underrepresented among available atomic-resolution structures. The use of detergents in protein purification procedures hinders the formation of well-ordered crystals for X-ray crystallography and leads to slower molecular tumbling, impeding the application of solution-state NMR. Solid-state magic-angle spinning NMR spectroscopy is an emerging method for membrane-protein structural biology that can overcome these technical problems. Here we present the solid-state NMR structure of the transmembrane domain of the Yersinia enterocolitica adhesin A (YadA). The sample was derived from crystallization trials that yielded only poorly diffracting microcrystals. We solved the structure using a single, uniformly 13C- and 15N-labeled sample. In addition, solid-state NMR allowed us to acquire information on the flexibility and mobility of parts of the structure, which, in combination with evolutionary conservation information, presents new insights into the autotransport mechanism of YadA.

Structure Calculation from Unambiguous Long-Range Amide and Methyl 1H−1H Distance Restraints for a Microcrystalline Protein with MAS Solid-State NMR Spectroscopy

Magic-angle spinning (MAS) solid-state NMR becomes an increasingly important tool for the determination of structures of membrane proteins and amyloid fibrils. Extensive deuteration of the protein allows multidimensional experiments with exceptionally high sensitivity and resolution to be obtained. Here we present an experimental strategy to measure highly unambiguous spatial correlations for distances up to 13 Å. Two complementary three-dimensional experiments, or alternatively a four-dimensional experiment, yield highly unambiguous cross-peak assignments, which rely on four encoded chemical shift dimensions. Correlations to residual aliphatic protons are accessible via synchronous evolution of the (15)N and (13)C chemical shifts, which encode valuable amide-methyl distance restraints. On average, we obtain six restraints per residue. Importantly, 50% of all restraints correspond to long-range distances between residues i and j with |i - j| > 5, which are of particular importance in structure calculations. Using ARIA, we calculate a high-resolution structure for the microcrystalline 7.2 kDa α-spectrin SH3 domain with a backbone precision of ∼1.1 Å.

Biogenesis and structure of a type VI secretion membrane core complex

Bacteria share their ecological niches with other microbes. The bacterial type VI secretion system is one of the key players in microbial competition, as well as being an important virulence determinant during bacterial infections. It assembles a nano-crossbow-like structure in the cytoplasm of the attacker cell that propels an arrow made of a haemolysin co-regulated protein (Hcp) tube and a valine–glycine repeat protein G (VgrG) spike and punctures the prey’s cell wall. The nano-crossbow is stably anchored to the cell envelope of the attacker by a membrane core complex. Here we show that this complex is assembled by the sequential addition of three type VI subunits (Tss)—TssJ, TssM and TssL—and present a structure of the fully assembled complex at 11.6 Å resolution, determined by negative-stain electron microscopy. With overall C5 symmetry, this 1.7-megadalton complex comprises a large base in the cytoplasm. It extends in the periplasm via ten arches to form a double-ring structure containing the carboxy-terminal domain of TssM (TssMct) and TssJ that is anchored in the outer membrane. The crystal structure of the TssMct–TssJ complex coupled to whole-cell accessibility studies suggest that large conformational changes induce transient pore formation in the outer membrane, allowing passage of the attacking Hcp tube/VgrG spike.

A software framework for analysing solid-state MAS NMR data

Solid-state magic-angle-spinning (MAS) NMR of proteins has undergone many rapid methodological developments in recent years, enabling detailed studies of protein structure, function and dynamics. Software development, however, has not kept pace with these advances and data analysis is mostly performed using tools developed for solution NMR which do not directly address solid-state specific issues. Here we present additions to the CcpNmr Analysis software package which enable easier identification of spinning side bands, straightforward analysis of double quantum spectra, automatic consideration of non-uniform labelling schemes, as well as extension of other existing features to the needs of solid-state MAS data. To underpin this, we have updated and extended the CCPN data model and experiment descriptions to include transfer types and nomenclature appropriate for solid-state NMR experiments, as well as a set of experiment prototypes covering the experiments commonly employed by solid-sate MAS protein NMR spectroscopists. This work not only improves solid-state MAS NMR data analysis but provides a platform for anyone who uses the CCPN data model for programming, data transfer, or data archival involving solid-state MAS NMR data.

CASD-NMR: Critical Assessment of Automated Structure Determination by NMR

We report the completion of the first comparison of automated NMR protein structure calculation methods and announce its continuation in the form of an ongoing, community-wide experiment: CASD-NMR (Critical Assessment of Automated Structure Determination of Proteins by NMR). CASD-NMR is open for any laboratory to participate and/or to submit targets. n nNMR spectroscopy is the only technique for the determination of the solution structure of biological macromolecules. This typically requires both the assignment of resonances and a labor-intensive analysis of multidimensional NOESY spectra, where peaks are matched to assigned resonances. Software tools for the full automation of the NOESY assignment and the structure calculation steps have the potential to boost the efficiency, reproducibility and reliability of NMR structures. Within the e-NMR project (www.e-nmr.eu), which is funded by the European Commission (Project number 213010), we are developing an approach to assess whether such automated methods can indeed produce structures that closely match those manually refined using the same experimental data (the “reference structures”). The concept closely resembles that of other community-wide experiments, such as CASP, the Critical Assessment of Techniques for Protein Structure Prediction1, and CAPRI, the Critical Assessment of Prediction of Interactions2. At variance with both CASP and CAPRI, CASD-NMR is entirely based on experimental data, presenting special issues in assembling, organizing, and distributing these data among participants. n nWe provided seven research teams in the field with ten experimental data sets for various protein systems of known structure and two sets for protein structures not yet publicly available (“blind tests”), courtesy of the NorthEast Structural Genomics consortium (NESG). We then met in Florence, Italy on May 4–6, 2009 to analyze the structures generated (Fig. 1), by comparison to the reference structures and by using software tools for structure validation. This first experiment indicated that while most submissions had correct overall folds, on certain targets some programs failed to calculate accurate packing and length of secondary structure elements. The root mean square deviations (RMSDs) of the backbone coordinates from the manually-solved structures were typically in the 1–2 A range, but reached values as high as 9 A in some cases. n n n nFigure 1 n nPerformance of various automated structure calculation methods

The chaperone αB-crystallin uses different interfaces to capture an amorphous and an amyloid client

Small heat-shock proteins, including αB-crystallin (αB), play an important part in protein homeostasis, because their ATP-independent chaperone activity inhibits uncontrolled protein aggregation. Mechanistic details of human αB, particularly in its client-bound state, have been elusive so far, owing to the high molecular weight and the heterogeneity of these complexes. Here we provide structural insights into this highly dynamic assembly and show, by using state-of-the-art NMR spectroscopy, that the αB complex is assembled from asymmetric building blocks. Interaction studies demonstrated that the fibril-forming Alzheimers disease Aβ1–40 peptide preferentially binds to a hydrophobic edge of the central β-sandwich of αB. In contrast, the amorphously aggregating client lysozyme is captured by the partially disordered N-terminal domain of αB. We suggest that αB uses its inherent structural plasticity to expose distinct binding interfaces and thus interact with a wide range of structurally variable clients.