Extending Native Top-Down Electron Capture Dissociation to MDa Immunoglobulin Complexes Provides Useful Sequence Tags Covering Their Critical Variable Complementarity-Determining Regions.
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ABSTRACT: Native top-down mass spectrometry (MS) is gaining traction for the analysis and sequencing of intact proteins and protein assemblies, giving access to their mass and composition, as well as sequence information useful for identification. Herein, we extend and apply native top-down MS, using electron capture dissociation, to two submillion Da IgM- and IgG-based oligomeric immunoglobulins. Despite structural similarities, these two systems are quite different. The ∼895 kDa noncovalent IgG hexamer consists of six IgG subunits hexamerizing in solution due to three specifically engineered mutations in the Fc region, whereas the ∼935 kDa IgM oligomer results from the covalent assembly of one joining (J) chain and 5 IgM subunits into an asymmetric "pentamer" stabilized by interchain disulfide bridges. Notwithstanding their size, structural differences, and complexity, we observe that their top-down electron capture dissociation spectra are quite similar and straightforward to interpret, specifically providing informative sequence tags covering the highly variable CDR3s and FR4s of the Ig subunits they contain. Moreover, we show that the electron capture dissociation fragmentation spectra of immunoglobulin oligomers are essentially identical to those obtained for their respective monomers. Demonstrated for recombinantly produced systems, the approach described here opens up new prospects for the characterization and identification of IgMs circulating in plasma, which is important since IgMs play a critical role in the early immune response to pathogens such as viruses and bacteria.
Project description:B lymphocytes play a pivotal role in multiple sclerosis pathology, possibly via both antibody-dependent and -independent pathways. Intrathecal immunoglobulin G in multiple sclerosis is produced by clonally expanded B-cell populations. Recent studies indicate that the complementarity determining regions of immunoglobulins specific for certain antigens are frequently shared between different individuals. In this study, our main objective was to identify specific proteomic profiles of mutated complementarity determining regions of immunoglobulin G present in multiple sclerosis patients but absent in healthy controls. To achieve this objective, we purified immunoglobulin G from the cerebrospinal fluid of 29 multiple sclerosis patients and 30 healthy controls and separated the corresponding heavy and light chains via SDS-PAGE. Subsequently, bands were excised, trypsinized, and measured with high-resolution mass spectrometry. We sequenced 841 heavy and 771 light chain variable region peptides. We observed 24 heavy and 26 light chain complementarity determining regions that were solely present in a number of multiple sclerosis patients. Using stringent criteria for the identification of common peptides, we found five complementarity determining regions shared in three or more patients and not in controls. Interestingly, one complementarity determining region with a single mutation was found in six patients. Additionally, one other patient carrying a similar complementarity determining region with another mutation was observed. In addition, we found a skew in the ?-to-? ratio and in the usage of certain variable heavy regions that was previously observed at the transcriptome level. At the protein level, cerebrospinal fluid immunoglobulin G shares common characteristics in the antigen binding region among different multiple sclerosis patients. The indication of a shared fingerprint may indicate common antigens for B-cell activation.
Project description:We have investigated four secretion-deficient antibodies (Abs) derived from a panel of 46 mutant T15 anti-phosphocholine Abs, all of which have point mutations in the heavy chain (H) complementarity determining region 2 (CDR2). The level of secretion for these four Abs was < 10% of wild type when expressed together with the T15 light chain (L) in either SP2/0 or P3X63Ag8.653 myeloma cells although normal levels of H and L chain mRNA were produced. Moreover, abundant intracellular H and L chain proteins were detected. Three of the four mutants had little or no assembled H and L complexes intracellularly whereas one had a significant amount of intracellular immunoglobulin (Ig) which was shown to be capable of binding Ag. Thus, we demonstrate for the first time that point mutations confined to CDR2 of the H chain variable (V) region can impede Ab assembly and secretion. We then introduced the same CDR2 mutations into a related H chain which is encoded by the same T15 VH gene but different diversity (D) and joining (J) genes. When these H chains were expressed with a non-T15 L chain, the resulting Abs were secreted normally. The results thus suggest that the effects of the CDR2 mutations on Ab secretion are dependent on their interactions with L and/or H chain D-J sequences. These results also reveal a novel mechanism that could contribute to B cell wastage.
Project description:Immunoglobulins A (IgA) include some of the most abundant human antibodies and play an important role in defending mucosal surfaces against pathogens. The unique structural features of the heavy chain of IgA subclasses (called IgA1 and IgA2) enable them to polymerize via the joining J-chain, resulting in IgA dimers but also higher oligomers. While secretory sIgA oligomers are dominant in milk and saliva, IgAs exist primarily as monomers in serum. No method currently allows disentangling the millions of unique IgAs potentially present in the human antibody repertoire. Obtaining unambiguous sequence reads of their hypervariable antigen-binding regions is a prerequisite for IgA identification. We here report a mass spectrometric method that uses electron capture dissociation (ECD) to produce straightforward-to-read sequence ladders of the variable parts of both the light and heavy chains of IgA1s, in particular, of the functionally critical CDR3 regions. We directly compare the native top-down ECD spectra of a heavily and heterogeneously N- and O-glycosylated anti-CD20 IgA1, the corresponding N-glycosylated anti-CD20 IgG1, and their Fab parts. We show that while featuring very different MS1 spectra, the native top-down ECD MS2 spectra of all four species are nearly identical, with cleavages occurring specifically within the CDR3 and FR4 regions of both the heavy and light chain. From the sequence-informative ECD data of an intact glycosylated IgA1, we foresee that native top-down ECD will become a valuable complementary tool for the de novo sequencing of IgA1s from milk, saliva, or serum.
Project description:Immunoglobulin light chain (LC) amyloidosis is a life-threatening disease whose understanding and treatment is complicated by vast numbers of patient-specific mutations. To address molecular origins of the disease, we explored 14 patient-derived and engineered proteins related to κ1-family germline genes IGKVLD-33*01 and IGKVLD-39*01. Hydrogen-deuterium exchange mass spectrometry analysis of local conformational dynamics in full-length recombinant LCs and their fragments was integrated with studies of thermal stability, proteolytic susceptibility, amyloid formation, and amyloidogenic sequence propensities using spectroscopic, electron microscopic and bioinformatics tools. The results were mapped on the atomic structures of native and fibrillary proteins. Proteins from two κ1 subfamilies showed unexpected differences. Compared to their germline counterparts, amyloid LC related to IGKVLD-33*01 was less stable and formed amyloid faster, whereas amyloid LC related to IGKVLD-39*01 had similar stability and formed amyloid slower. These and other differences suggest different major factors influencing amyloid formation. In 33*01-related amyloid LC, these factors involved mutation-induced destabilization of the native structure and probable stabilization of amyloid. The atypical behavior of 39*01-related amyloid LC tracked back to increased dynamics/exposure of amyloidogenic segments in βC’V and βEV that could initiate aggregation, combined with decreased dynamics/exposure near the C23-Cys88 disulfide whose rearrangement is rate-limiting to amyloidogenesis. The results suggest distinct amyloidogenic pathways for closely related LCs and point to the antigen-binding regions CDR1 and CDR3, which are linked via the conserved internal disulfide, as key factors in amyloid formation by various LCs.
Project description:MOTIVATION:Accurate identification of peptides binding to specific Major Histocompatibility Complex Class II (MHC-II) molecules is of great importance for elucidating the underlying mechanism of immune recognition, as well as for developing effective epitope-based vaccines and promising immunotherapies for many severe diseases. Due to extreme polymorphism of MHC-II alleles and the high cost of biochemical experiments, the development of computational methods for accurate prediction of binding peptides of MHC-II molecules, particularly for the ones with few or no experimental data, has become a topic of increasing interest. TEPITOPE is a well-used computational approach because of its good interpretability and relatively high performance. However, TEPITOPE can be applied to only 51 out of over 700 known HLA DR molecules. METHOD:We have developed a new method, called TEPITOPEpan, by extrapolating from the binding specificities of HLA DR molecules characterized by TEPITOPE to those uncharacterized. First, each HLA-DR binding pocket is represented by amino acid residues that have close contact with the corresponding peptide binding core residues. Then the pocket similarity between two HLA-DR molecules is calculated as the sequence similarity of the residues. Finally, for an uncharacterized HLA-DR molecule, the binding specificity of each pocket is computed as a weighted average in pocket binding specificities over HLA-DR molecules characterized by TEPITOPE. RESULT:The performance of TEPITOPEpan has been extensively evaluated using various data sets from different viewpoints: predicting MHC binding peptides, identifying HLA ligands and T-cell epitopes and recognizing binding cores. Among the four state-of-the-art competing pan-specific methods, for predicting binding specificities of unknown HLA-DR molecules, TEPITOPEpan was roughly the second best method next to NETMHCIIpan-2.0. Additionally, TEPITOPEpan achieved the best performance in recognizing binding cores. We further analyzed the motifs detected by TEPITOPEpan, examining the corresponding literature of immunology. Its online server and PSSMs therein are available at http://www.biokdd.fudan.edu.cn/Service/TEPITOPEpan/.
Project description:The increasing importance of immunoglobulins G (IgGs) as biotherapeutics calls for improved structural characterization methods designed for these large (~150kDa) macromolecules. Analysis workflows have to be rapid, robust, and require minimal sample preparation. In a previous work we showed the potential of Orbitrap Fourier transform mass spectrometry (FTMS) combined with electron transfer dissociation (ETD) for the top-down investigation of an intact IgG1, resulting in ~30% sequence coverage. Here, we describe a top-down analysis of two IgGs1 (adalimumab and trastuzumab) and one IgG2 (panitumumab) performed with ETD on a mass spectrometer equipped with a high-field Orbitrap mass analyzer. For the IgGs1, sequence coverage comparable to the previous results was achieved in a two-fold reduced number of summed transients, which corresponds, taken together with the significantly increased spectra acquisition rate, to ~six-fold improvement in analysis time. Furthermore, we studied the influence of ion-ion interaction times on ETD product ions for IgGs1, and the differences in fragmentation behavior between IgGs1 and IgG2, which present structural differences. Overall, these results reinforce the hypothesis that gas phase dissociation using both energy threshold-based and radical-driven ion activations is directed to specific regions of the polypeptide chains mostly by the location of disulfide bonds.Significance of the studyCompared with our previous report, the results presented herein demonstrate the power of technological advances of the next generation Orbitrap™ platform, including the use of a high-field compact (i.e., D20) Orbitrap mass analyzer, and a dedicated manipulation strategy for large protein ions (via their trapping in the HCD collision cell along with reduction of the pressure in the cell). Notably, these important developments became recently commercially available in the top-end Orbitrap platforms under the name of "Protein Mode". Furthermore, we continued exploring the advantages offered by the summation (averaging) of transients (time-domain data) for improving the signal-to-noise ratio of top-down mass spectra. Finally, for the first time we report the application of the hybrid ion activation technique that combines electron transfer dissociation and higher energy collisional dissociation, known as EThcD, on intact monoclonal antibodies. Under these specific instrumental parameters, EThcD produces a partially complementary fragmentation pattern compared to ETD, increasing the overall sequence coverage especially at the protein termini.
Project description:The data presented in this article are related to the research article entitled "Development of IgY antibodies against anti-snake toxins endowed with highly lethal neutralizing activity" (da Rocha et al., 2017) [1]. Complementarity-determining region (CDR) sequences are variable antibody (Ab) sequences that respond with specificity, duration and strength to identify and bind to antigen (Ag) epitopes. B lymphocytes isolated from hens immunized with Bitis arietans (Ba) and anti-Crotalus durissus terrificus (Cdt) venoms and expressing high specificity, affinity and toxicity neutralizing antibody titers were used as DNA sources. The VLF1, CDR1, CDR2, VLR1 and CDR3 sequences were validated by BLASTp, and values corresponding to IgY VL and VH anti-Ba or anti-Cdt venoms were identified, registered [Gallus gallus IgY Fv Light chain (GU815099)/Gallus gallus IgY Fv Heavy chain (GU815098)] and used for molecular modeling of IgY scFv anti-Ba. The resulting CDR1, CDR2 and CDR3 sequences were combined to construct the three - dimensional structure of the Ab paratope.
Project description:Chimeric antigen receptor (CAR)-T cell therapy is rapidly advancing as cancer treatment, however, designing an optimal CAR remains challenging. A single-chain variable fragment (scFv) is generally used as CAR targeting moiety, wherein the complementarity-determining regions (CDRs) define its specificity. We report here that the CDR loops can cause CAR clustering, leading to antigen-independent tonic signalling and subsequent CAR-T cell dysfunction. We show via CARs incorporating scFvs with identical framework and varying CDR sequences that CARs may cluster on the T cell surface, which leads to antigen-independent CAR-T cell activation, characterized by increased cell size and interferon (IFN)-γ secretion. This results in CAR-T cell exhaustion, activation-induced cell death and reduced responsiveness to target-antigen-expressing tumour cells. CDR mutagenesis confirms that the CAR-clustering is mediated by CDR-loops. In summary, antigen-independent tonic signalling can be induced by CDR-mediated CAR clustering, which could not be predicted from the scFv sequences, but could be tested for by evaluating the activity of unstimulated CAR-T cells.
Project description:MOTIVATION:The precise targeting of antibodies and other protein therapeutics is required for their proper function and the elimination of deleterious off-target effects. Often the molecular structure of a therapeutic target is unknown and randomized methods are used to design antibodies without a model that relates antibody sequence to desired properties. RESULTS:Here, we present Ens-Grad, a machine learning method that can design complementarity determining regions of human Immunoglobulin G antibodies with target affinities that are superior to candidates derived from phage display panning experiments. We also demonstrate that machine learning can improve target specificity by the modular composition of models from different experimental campaigns, enabling a new integrative approach to improving target specificity. Our results suggest a new path for the discovery of therapeutic molecules by demonstrating that predictive and differentiable models of antibody binding can be learned from high-throughput experimental data without the need for target structural data. AVAILABILITY AND IMPLEMENTATION:Sequencing data of the phage panning experiment are deposited at NIH's Sequence Read Archive (SRA) under the accession number SRP158510. We make our code available at https://github.com/gifford-lab/antibody-2019. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
Project description:Classification of antibody complementarity-determining region (CDR) conformations is an important step that drives antibody modelling and engineering, prediction from sequence, directed mutagenesis and induced-fit studies, and allows inferences on sequence-to-structure relations. Most of the previous work performed conformational clustering on a reduced set of structures or after application of various structure pre-filtering criteria. In this study, it was judged that a clustering of every available CDR conformation would produce a complete and redundant repertoire, increase the number of sequence examples and allow better decisions on structure validity in the future. In order to cope with the potential increase in data noise, a first-level statistical clustering was performed using structure superposition Root-Mean-Square Deviation (RMSD) as a distance-criterion, coupled with second- and third-level clustering that employed Ramachandran regions for a deeper qualitative classification. The classification of a total of 12,712 CDR conformations is thus presented, along with rich annotation and cluster descriptions, and the results are compared to previous major studies. The present repertoire has procured an improved image of our current CDR Knowledge-Base, with a novel nesting of conformational sensitivity and specificity that can serve as a systematic framework for improved prediction from sequence as well as a number of future studies that would aid in knowledge-based antibody engineering such as humanisation.