Structures of Pathological and Functional Amyloids and Prions, a Solid-State NMR Perspective.

Infectious proteins or prions are a remarkable class of pathogens, where pathogenicity and infectious state correspond to conformational transition of a protein fold. The conformational change translates into the formation by the protein of insoluble amyloid aggregates, associated in humans with various neurodegenerative disorders and systemic protein-deposition diseases. The prion principle, however, is not limited to pathogenicity. While pathological amyloids (and prions) emerge from protein misfolding, a class of functional amyloids has been defined, consisting of amyloid-forming domains under natural selection and with diverse biological roles. Although of great importance, prion amyloid structures remain challenging for conventional structural biology techniques. Solid-state nuclear magnetic resonance (SSNMR) has been preferentially used to investigate these insoluble, morphologically heterogeneous aggregates with poor crystallinity. SSNMR methods have yielded a wealth of knowledge regarding the fundamentals of prion biology and have helped to solve the structures of several prion and prion-like fibrils. Here, we will review pathological and functional amyloid structures and will discuss some of the obtained structural models. We will finish the review with a perspective on integrative approaches combining solid-state NMR, electron paramagnetic resonance and cryo-electron microscopy, which can complement and extend our toolkit to structurally explore various facets of prion biology.

Probing the Conformational Dynamics of Affinity-Enhanced T Cell Receptor Variants upon Binding the Peptide-Bound Major Histocompatibility Complex by Hydrogen/Deuterium Exchange Mass Spectrometry.

Binding of the T cell receptor (TCR) to its cognate, peptide antigen-loaded major histocompatibility complex (pMHC) is a key interaction for triggering T cell activation and ultimately elimination of the target cell. Despite the importance of this interaction for cellular immunity, a comprehensive molecular understanding of TCR specificity and affinity is lacking. We conducted hydrogen/deuterium exchange mass spectrometry (HDX-MS) analyses of individual affinity-enhanced TCR variants and clinically relevant pMHC class I molecules (HLA-A*0201/NY-ESO-1157-165) to investigate the causality between increased binding affinity and conformational dynamics in TCR-pMHC complexes. Differential HDX-MS analyses of TCR variants revealed that mutations for affinity enhancement in TCR CDRs altered the conformational response of TCR to pMHC ligation. Improved pMHC binding affinity was in general observed to correlate with greater differences in HDX upon pMHC binding in modified TCR CDR loops, thereby providing new insights into the TCR-pMHC interaction. Furthermore, a specific point mutation in the ß-CDR3 loop of the NY-ESO-1 TCR associated with a substantial increase in binding affinity resulted in a substantial change in pMHC binding kinetics (i.e., very slow kon, revealed by the detection of EX1 HDX kinetics), thus providing experimental evidence for a slow induced-fit binding mode. We also examined the conformational impact of pMHC binding on an unrelated TRAV12-2 gene-encoded TCR directed against the immunodominant MART-126-35 cancer antigen restricted by HLA-A*0201. Our findings provide a molecular basis for the observed TRAV12-2 gene bias in natural CD8+ T cell-based immune responses against the MART-1 antigen, with potential implications for general ligand discrimination and TCR cross-reactivity processes.

The T-Cell Receptor Can Bind to the Peptide-Bound Major Histocompatibility Complex and Uncomplexed ß2-Microglobulin through Distinct Binding Sites.

T-Cell receptor (TCR)-mediated recognition of the peptide-bound major histocompatibility complex (pMHC) initiates an adaptive immune response against antigen-presenting target cells. The recognition events take place at the TCR-pMHC interface, and their effects on TCR conformation and dynamics are controversial. Here, we have measured the time-resolved hydrogen/deuterium exchange (HDX) of a soluble TCR in the presence and absence of its cognate pMHC by mass spectrometry to delineate the impact of pMHC binding on solution-phase structural dynamics in the TCR. Our results demonstrate that while TCR-pMHC complex formation significantly stabilizes distinct CDR loops of the TCR, it does not trigger structural changes in receptor segments remote from the binding interface. Intriguingly, our HDX measurements reveal that the TCR α-constant domain (C- and F-strand) directly interacts with the unbound MHC light chain, ß2-microglobulin (ß2m). Surface plasmon resonance measurements corroborated a binding event between TCR and ß2m with a dissociation constant of 167 ± 20 µM. We propose a model structure for the TCR-ß2m complex based on a refined protein-protein docking approach driven by HDX data and information from molecular dynamics simulations. Using a biological assay based on TCR gene-engineered primary human T cells, we did not observe a significant effect of ß2m on T-cell cytotoxicity, suggesting an alternate role for ß2m binding. Overall, we show that binding of ß2m to the TCR occurs in vitro and, as such, not only should be considered in structure-function studies of the TCR-pMHC complex but also could play a hitherto unidentified role in T-cell function in vivo.

Automated structure modeling of large protein assemblies using crosslinks as distance restraints.

Crosslinking mass spectrometry is increasingly used for structural characterization of multisubunit protein complexes. Chemical crosslinking captures conformational heterogeneity, which typically results in conflicting crosslinks that cannot be satisfied in a single model, making detailed modeling a challenging task. Here we introduce an automated modeling method dedicated to large protein assemblies ('XL-MOD' software is available at http://aria.pasteur.fr/supplementary-data/x-links) that (i) uses a form of spatial restraints that realistically reflects the distribution of experimentally observed crosslinked distances; (ii) automatically deals with ambiguous and/or conflicting crosslinks and identifies alternative conformations within a Bayesian framework; and (iii) allows subunit structures to be flexible during conformational sampling. We demonstrate our method by testing it on known structures and available crosslinking data. We also crosslinked and modeled the 17-subunit yeast RNA polymerase III at atomic resolution; the resulting model agrees remarkably well with recently published cryoelectron microscopy structures and provides additional insights into the polymerase structure.

Neisseria meningitidis Type IV Pili Composed of Sequence Invariable Pilins Are Masked by Multisite Glycosylation.

The ability of pathogens to cause disease depends on their aptitude to escape the immune system. Type IV pili are extracellular filamentous virulence factors composed of pilin monomers and frequently expressed by bacterial pathogens. As such they are major targets for the host immune system. In the human pathogen Neisseria meningitidis, strains expressing class I pilins contain a genetic recombination system that promotes variation of the pilin sequence and is thought to aid immune escape. However, numerous hypervirulent clinical isolates express class II pilins that lack this property. This raises the question of how they evade immunity targeting type IV pili. As glycosylation is a possible source of antigenic variation it was investigated using top-down mass spectrometry to provide the highest molecular precision on the modified proteins. Unlike class I pilins that carry a single glycan, we found that class II pilins display up to 5 glycosylation sites per monomer on the pilus surface. Swapping of pilin class and genetic background shows that the pilin primary structure determines multisite glycosylation while the genetic background determines the nature of the glycans. Absence of glycosylation in class II pilins affects pilus biogenesis or enhances pilus-dependent aggregation in a strain specific fashion highlighting the extensive functional impact of multisite glycosylation. Finally, molecular modeling shows that glycans cover the surface of class II pilins and strongly decrease antibody access to the polypeptide chain. This strongly supports a model where strains expressing class II pilins evade the immune system by changing their sugar structure rather than pilin primary structure. Overall these results show that sequence invariable class II pilins are cloaked in glycans with extensive functional and immunological consequences.

An automatic tool to analyze and cluster macromolecular conformations based on self-organizing maps.

MOTIVATION: Sampling the conformational space of biological macromolecules generates large sets of data with considerable complexity. Data-mining techniques, such as clustering, can extract meaningful information. Among them, the self-organizing maps (SOMs) algorithm has shown great promise; in particular since its computation time rises only linearly with the size of the data set. Whereas SOMs are generally used with few neurons, we investigate here their behavior with large numbers of neurons. RESULTS: We present here a python library implementing the full SOM analysis workflow. Large SOMs can readily be applied on heavy data sets. Coupled with visualization tools they have very interesting properties. Descriptors for each conformation of a trajectory are calculated and mapped onto a 3D landscape, the U-matrix, reporting the distance between neighboring neurons. To delineate clusters, we developed the flooding algorithm, which hierarchically identifies local basins of the U-matrix from the global minimum to the maximum. AVAILABILITY AND IMPLEMENTATION: The python implementation of the SOM library is freely available on github: https://github.com/bougui505/SOM. CONTACT: michael.nilges@pasteur.fr or guillaume.bouvier@pasteur.fr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

T-cell receptors binding orientation over peptide/MHC class I is driven by long-range interactions.

Crystallographic data about T-Cell Receptor - peptide - major histocompatibility complex class I (TCRpMHC) interaction have revealed extremely diverse TCR binding modes triggering antigen recognition. Understanding the molecular basis that governs TCR orientation over pMHC is still a considerable challenge. We present a simplified rigid approach applied on all non-redundant TCRpMHC crystal structures available. The CHARMM force field in combination with the FACTS implicit solvation model is used to study the role of long-distance interactions between the TCR and pMHC. We demonstrate that the sum of the coulomb interactions and the electrostatic solvation energies is sufficient to identify two orientations corresponding to energetic minima at 0° and 180° from the native orientation. Interestingly, these results are shown to be robust upon small structural variations of the TCR such as changes induced by Molecular Dynamics simulations, suggesting that shape complementarity is not required to obtain a reliable signal. Accurate energy minima are also identified by confronting unbound TCR crystal structures to pMHC. Furthermore, we decompose the electrostatic energy into residue contributions to estimate their role in the overall orientation. Results show that most of the driving force leading to the formation of the complex is defined by CDR1,2/MHC interactions. This long-distance contribution appears to be independent from the binding process itself, since it is reliably identified without considering neither short-range energy terms nor CDR induced fit upon binding. Ultimately, we present an attempt to predict the TCR/pMHC binding mode for a TCR structure obtained by homology modeling. The simplicity of the approach and the absence of any fitted parameters make it also easily applicable to other types of macromolecular protein complexes.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vß chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3ß sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Distinct sets of alphabeta TCRs confer similar recognition of tumor antigen NY-ESO-1157-165 by interacting with its central Met/Trp residues.

Naturally acquired immune responses against human cancers often include CD8(+) T cells specific for the cancer testis antigen NY-ESO-1. Here, we studied T cell receptor (TCR) primary structure and function of 605 HLA-A*0201/NY-ESO-1(157-165)-specific CD8 T cell clones derived from five melanoma patients. We show that an important proportion of tumor-reactive T cells preferentially use TCR AV3S1/BV8S2 chains, with remarkably conserved CDR3 amino acid motifs and lengths in both chains. All remaining T cell clones belong to two additional sets expressing BV1 or BV13 TCRs, associated with alpha-chains with highly diverse VJ usage, CDR3 amino acid sequence, and length. Yet, all T cell clonotypes recognize tumor antigen with similar functional avidity. Two residues, Met-160 and Trp-161, located in the middle region of the NY-ESO-1(157-165) peptide, are critical for recognition by most of the T cell clonotypes. Collectively, our data show that a large number of alphabeta TCRs, belonging to three distinct sets (AVx/BV1, AV3/BV8, AVx/BV13) bind pMHC with equal antigen sensitivity and recognize the same peptide motif. Finally, this in-depth study of recognition of a self-antigen suggests that in part similar biophysical mechanisms shape TCR repertoires toward foreign and self-antigens.

A novel population of human melanoma-specific CD8 T cells recognizes Melan-AMART-1 immunodominant nonapeptide but not the corresponding decapeptide.

HLA-A2-restricted cytolytic T cells specific for the immunodominant human tumor Ag Melan-A(MART-1) can kill most HLA-matched melanoma cells, through recognition of two naturally occurring antigenic variants, i.e., Melan-A nonamer AAGIGILTV and decamer EAAGIGILTV peptides. Several previous studies have suggested a high degree of TCR cross-reactivity to the two peptides. In this study, we describe for the first time that some T cell clones are exclusively nonamer specific, because they are not labeled by A2/decamer-tetramers and do not recognize the decamer when presented endogenously. Functional assays with peptides gave misleading results, possibly because decamers were cleaved by exopeptidases. Interestingly, nonapeptide-specific T cell clones were rarely Valpha2.1 positive (only 1 of 19 clones), in contrast to the known strong bias for Valpha2.1-positive TCRs found in decamer-specific clones (59 of 69 clones). Molecular modeling revealed that nonapeptide-specific TCRs formed unfavorable interactions with the decapeptide, whereas decapeptide-specific TCRs productively created a hydrogen bond between CDR1alpha and glutamic acid (E) of the decapeptide. Ex vivo analysis of T cells from melanoma metastases demonstrated that both nonamer and decamer-specific T cells were enriched to substantial frequencies in vivo, and representative clones showed efficient tumor cell recognition and killing. We conclude that the two peptides should be regarded as distinct epitopes when analyzing tumor immunity and developing immunotherapy against melanoma.