Search

Background and Aims Development of a prophylactic hepatitis C virus (HCV) vaccine will require accurate and reproducible measurement of neutralizing breadth of vaccine-induced antibodies. Currently available HCV panels may not adequately represent the genetic and antigenic diversity of circulating HCV strains, and the lack of standardization of these panels makes it difficult to compare neutralization results obtained in different studies. Here, we describe the selection and validation of a genetically and antigenically diverse reference panel of 15 HCV pseudoparticles (HCVpp) for neutralization assays. Methods We chose 75 envelope (E1E2) clones to maximize representation of natural polymorphisms observed in circulating HCV isolates, and 65 of these clones generated functional HCVpp. Neutralization sensitivity of these HCVpp varied widely. HCVpp clustered into 15 distinct groups based on patterns of relative sensitivity to seven broadly neutralizing monoclonal antibodies (bNAbs). We used these data to select a final panel of 15 antigenically representative HCVpp. Results Both the 65 and 15 HCVpp panels span four tiers of neutralization sensitivity, and neutralizing breadth measurements for seven bNAbs were nearly equivalent using either panel. Differences in neutralization sensitivity between HCVpp were independent of genetic distances between E1E2 clones. Conclusions Neutralizing breadth of HCV antibodies should be defined using viruses spanning multiple tiers of neutralization sensitivity, rather than panels selected solely for genetic diversity. We propose that this multi-tier reference panel could be adopted as a standard for the measurement of neutralizing antibody potency and breadth, facilitating meaningful comparisons of neutralization results from vaccine studies in different laboratories.

The spike (S) protein of SARS-CoV-2 is delivered to the virion assembly site in the ER-Golgi Intermediate Compartment (ERGIC) from both the ER and cis-Golgi in infected cells1-3. However, the relevance and modulatory mechanism of this bidirectional trafficking are unclear. Here, using structure-function analyses, we show that S incorporation into virions and viral fusogenicity are determined by coatomer-dependent S delivery from the cis-Golgi and restricted by S-coatomer dissociation. Although S mimicry of the host coatomer-binding dibasic motif ensures retrograde trafficking to the ERGIC, avoidance of the host-like C-terminal acidic residue is critical for S-coatomer dissociation and therefore incorporation into virions or export for cell-cell fusion. Because this C-terminal residue is the key determinant of SARS-CoV-2 assembly and fusogenicity, our work provides a framework for the export of S protein encoded in genetic vaccines for surface display and immune activation.

High-resolution experimental structural determination of protein-protein interactions has led to valuable mechanistic insights, yet due to the massive number of interactions and experimental limitations there is a need for computational methods that can accurately model their structures. Here we explore the use of the recently developed deep learning method, AlphaFold, to predict structures of protein complexes from sequence. With a benchmark of 152 diverse heterodimeric protein complexes, multiple implementations and parameters of AlphaFold were tested for accuracy. Remarkably, many cases (43%) had near-native models (medium or high critical assessment of predicted interactions accuracy) generated as top-ranked predictions by AlphaFold, greatly surpassing the performance of unbound protein-protein docking (9% success rate for near-native top-ranked models), however AlphaFold modeling of antibody-antigen complexes within our set was unsuccessful. We identified sequence and structural features associated with lack of AlphaFold success, and we also investigated the impact of multiple sequence alignment input. Benchmarking of a multimer-optimized version of AlphaFold (AlphaFold-Multimer) with a set of recently released antibody-antigen structures confirmed a low rate of success for antibody-antigen complexes (11% success), and we found that T cell receptor-antigen complexes are likewise not accurately modeled by that algorithm, showing that adaptive immune recognition poses a challenge for the current AlphaFold algorithm and model. Overall, our study demonstrates that end-to-end deep learning can accurately model many transient protein complexes, and highlights areas of improvement for future developments to reliably model any protein-protein interaction of interest.

Enterotoxigenic Escherichia coli (ETEC) is estimated to cause approximately 380,000 deaths annually during sporadic or epidemic outbreaks worldwide. Development of vaccines against ETEC is very challenging due to the vast heterogeneity of the ETEC strains. An effective vaccines would have to be multicomponent to provide coverage of over ten ETEC strains with genetic variabilities. There is currently no vaccine licensed to prevent ETEC. Nanobodies are successful new biologics in treating mucosal infectious disease as they recognize conserved epitopes on hypervariable pathogens. Cocktails consisting of multiple nanobodies could provide even broader epitope coverage at a lower cost compared to monoclonal antibodies. Identification of conserved epitopes by nanobodies can also assist reverse engineering of an effective vaccine against ETEC. By screening nanobodies from immunized llamas and a naïve yeast display library against adhesins of colonization factors, we identified single nanobodies that show cross-protective potency against eleven major pathogenic ETEC strains in vitro. Oral administration of nanobodies led to a significant reduction of bacterial colonization in animals. Moreover, nanobody-IgA fusion showed extended inhibitory activity in mouse colonization compared to commercial hyperimmune bovine colostrum product used for prevention of ETEC-induced diarrhea. Structural analysis revealed that nanobodies recognized a highly-conserved epitope within the putative receptor binding region of ETEC adhesins. Our findings support further rational design of a pan-ETEC vaccine to elicit robust immune responses targeting this conserved epitope.

Motivation The binding of T-cell receptors (TCRs) to their target peptide MHC (pMHC) ligands initializes the cell-mediated immune response. In autoimmune diseases such as multiple sclerosis, the TCR erroneously recognizes self-peptides as foreign and activates an immune response against healthy cells. Such responses can be triggered by cross-recognition of the autoreactive TCR with foreign peptides. Hence, it would be desirable to identify such foreign-antigen triggers to provide a mechanistic understanding of autoimmune diseases. However, the large sequence space of foreign antigens presents an obstacle in the identification of cross-reactive peptides. Results Here, we present an in silico modeling and scoring method which exploits the structural properties of TCR-pMHC complexes to predict the binding of cross-reactive peptides. We analyzed three mouse TCRs and one human TCR isolated from a patient with multiple sclerosis. Cross-reactive peptides for these TCRs were previously identified via yeast display coupled with deep sequencing, providing a robust dataset for evaluating our method. Modeling query peptides in their associated TCR-pMHC crystal structures, our method accurately selected the top binding peptides from sets containing more than a hundred thousand unique peptides. Availability and implementation Analyses were performed using custom Python and R scripts available at https://github.com/weng-lab/antigen-predict. Supplementary information Supplementary data are available at Bioinformatics online.

SARS-CoV-2, the etiologic agent of COVID-19, exemplifies the general threat to global health posed by coronaviruses. The urgent need for effective vaccines and therapies is leading to a rapid rise in the number of high resolution structures of SARS-CoV-2 proteins that collectively reveal a map of virus vulnerabilities. To assist structure-based design of vaccines and therapeutics against SARS-CoV-2 and other coronaviruses, we have developed CoV3D, a database and resource for coronavirus protein structures, which is updated on a weekly basis. CoV3D provides users with comprehensive sets of structures of coronavirus proteins and their complexes with antibodies, receptors, and small molecules. Integrated molecular viewers allow users to visualize structures of the spike glycoprotein, which is the major target of neutralizing antibodies and vaccine design efforts, as well as sets of spike-antibody complexes, spike sequence variability, and known polymorphisms. In order to aid structure-based design and analysis of the spike glycoprotein, CoV3D permits visualization and download of spike structures with modeled N-glycosylation at known glycan sites, and contains structure-based classification of spike conformations, generated by unsupervised clustering. CoV3D can serve the research community as a centralized reference and resource for spike and other coronavirus protein structures, and is available at: https://cov3d.ibbr.umd.edu., Graphical Abstract Graphical AbstractCoV3D: a database of high resolution coronavirus protein structures.

Two well-defined synthetic polyphosphazene immunoadjuvants, PCPP and PCEP, were studied for their ability to potentiate the immune response to the hepatitis C virus (HCV) E2 glycoprotein antigen in vivo. We report that PCEP induced significantly higher serum neutralization and HCV-specific IgG titers in mice compared to other adjuvants used in the study: PCPP, Alum, and Addavax. PCEP also shifted the response toward the desirable balanced Th1/Th2 immunity, as evaluated by the antibody isotype ratio (IgG2a/IgG1). The in vivo results were analyzed in the context of antigen-adjuvant molecular interactions in the system and in vitro immunostimulatory activity of formulations. Asymmetric flow field flow fractionation (AF4) and dynamic light scattering (DLS) analysis showed that both PCPP and PCEP spontaneously self-assemble with the E2 glycoprotein with the formation of multimeric water-soluble complexes, which demonstrates the role of polyphosphazene macromolecules as vaccine delivery vehicles. Intrinsic in vitro immunostimulatory activity of polyphosphazene adjuvants, which was assessed using a mouse macrophage cell line, revealed comparable activities of both polymers and did not provide an explanation of their in vivo performance. However, PCEP complexes with E2 displayed greater stability against agglomeration and improved in vitro immunostimulatory activity compared to those of PCPP, which is in line with superior in vivo performance of PCEP. The results emphasize the importance of often neglected antigen-polyphosphazene self-assembly mechanisms in formulations, which can provide important insights on their in vivo behavior and facilitate the establishment of a structure-activity relationship for this important class of immunoadjuvants.

Primary cutaneous γδ T cell lymphomas (PCGDTLs) represent a heterogeneous group of uncommon but aggressive cancers. Herein, we perform genome-wide DNA, RNA, and T cell receptor (TCR) sequencing on 29 cutaneous γδ lymphomas. We find that PCGDTLs are not uniformly derived from Vδ2 cells. Instead, the cell-of-origin depends on the tissue compartment from which the lymphomas are derived. Lymphomas arising from the outer layer of skin are derived from Vδ1 cells, the predominant γδ cell in the epidermis and dermis. In contrast, panniculitic lymphomas arise from Vδ2 cells, the predominant γδ T cell in the fat. We also show that TCR chain usage is non-random, suggesting common antigens for Vδ1 and Vδ2 lymphomas respectively. In addition, Vδ1 and Vδ2 PCGDTLs harbor similar genomic landscapes with potentially targetable oncogenic mutations in the JAK/STAT, MAPK, MYC, and chromatin modification pathways. Collectively, these findings suggest a paradigm for classifying, staging, and treating these diseases., Cutaneous gamma-delta T cell lymphomas are rare but aggressive cancers. Here, by DNA, RNA and T cell receptor sequencing, the authors elucidate the molecular ontogeny by revising the cell of origin and identifying potentially targetable mutations.

Significance Hepatitis C virus chronically infects approximately 1% of the world’s population, making an effective vaccine for hepatitis C virus a major unmet public health need. The membrane-associated E1E2 envelope glycoprotein has been used in clinical studies as a vaccine candidate. However, limited neutralization breadth and difficulty in producing large amounts of homogeneous membrane-associated E1E2 have hampered efforts to develop an E1E2-based vaccine. Our previous work described the design and biochemical validation of a native-like soluble secreted form of E1E2 (sE1E2). Here, we describe the immunogenic characterization of the sE1E2 complex. sE1E2 elicited broadly neutralizing antibodies in immunized mice, with increased neutralization breadth relative to the membrane-associated E1E2, thereby validating this platform as a promising model system for vaccine development.

We present the results for CAPRI Round 50, the fourth joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of twelve targets, including six dimers, three trimers, and three higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly related templates were found for the individual subunits. Twenty-five CAPRI groups including eight automatic servers submitted ~1250 models per target. Twenty groups including six servers participated in the CAPRI scoring challenge submitted ~190 models per target. The accuracy of the predicted models was evaluated using the classical CAPRI criteria. The prediction performance was measured by a weighted scoring scheme that takes into account the number of models of acceptable quality or higher submitted by each group as part of their five top-ranking models. Compared to the previous CASP-CAPRI challenge, top performing groups submitted such models for a larger fraction (70–75%) of the targets in this Round, but fewer of these models were of high accuracy. Scorer groups achieved stronger performance with more groups submitting correct models for 70–80% of the targets or achieving high accuracy predictions. Servers performed less well in general, except for the MDOCKPP and LZERD servers, who performed on par with human groups. In addition to these results, major advances in methodology are discussed, providing an informative overview of where the prediction of protein assemblies currently stands., Cancer Research UK, Grant/Award Number: FC001003; Changzhou Science and Technology Bureau, Grant/Award Number: CE20200503; Department of Energy and Climate Change, Grant/Award Numbers: DE-AR001213, DE-SC0020400, DE-SC0021303; H2020 European Institute of Innovation and Technology, Grant/Award Numbers: 675728, 777536, 823830; Institut national de recherche en informatique et en automatique (INRIA), Grant/Award Number: Cordi-S; Lietuvos Mokslo Taryba, Grant/Award Numbers: S-MIP-17-60, S-MIP-21-35; Medical Research Council, Grant/Award Number: FC001003; Japan Society for the Promotion of Science KAKENHI, Grant/Award Number: JP19J00950; Ministerio de Ciencia e Innovación, Grant/Award Number: PID2019-110167RB-I00; Narodowe Centrum Nauki, Grant/Award Numbers: UMO-2017/25/B/ST4/01026, UMO-2017/26/M/ST4/00044, UMO-2017/27/B/ST4/00926; National Institute of General Medical Sciences, Grant/Award Numbers: R21GM127952, R35GM118078, RM1135136, T32GM132024; National Institutes of Health, Grant/Award Numbers: R01GM074255, R01GM078221, R01GM093123, R01GM109980, R01GM133840, R01GN123055, R01HL142301, R35GM124952, R35GM136409; National Natural Science Foundation of China, Grant/Award Number: 81603152; National Science Foundation, Grant/Award Numbers: AF1645512, CCF1943008, CMMI1825941, DBI1759277, DBI1759934, DBI1917263, DBI20036350, IIS1763246, MCB1925643; NWO, Grant/Award Number: TOP-PUNT 718.015.001; Wellcome Trust, Grant/Award Number: FC001003

Adoptive cell therapy with tumor-specific T cells can mediate durable cancer regression. The prime target of tumor-specific T cells are neoantigens arising from mutations in self-proteins during malignant transformation. To understand T cell recognition of cancer neoantigens at the atomic level, we studied oligoclonal T cell receptors (TCRs) that recognize a neoepitope arising from a driver mutation in the p53 oncogene (p53R175H) presented by the major histocompatibility complex class I molecule HLA-A2. We previously reported the structures of three p53R175H-specific TCRs (38-10, 12-6, and 1a2) bound to p53R175H and HLA-A2. The structures showed that these TCRs discriminate between WT and mutant p53 by forming extensive interactions with the R175H mutation. Here, we report the structure of a fourth p53R175H-specific TCR (6-11) in complex with p53R175H and HLA-A2. In contrast to 38-10, 12-6, and 1a2, TCR 6-11 makes no direct contacts with the R175H mutation, yet is still able to distinguish mutant from WT p53. Structure-based in silico mutagenesis revealed that the 60-fold loss in 6-11 binding affinity for WT p53 compared to p53R175H is mainly due to the higher energetic cost of desolvating R175 in the WT p53 peptide during complex formation than H175 in the mutant. This indirect strategy for preferential neoantigen recognition by 6-11 is fundamentally different from the direct strategies employed by other TCRs and highlights the multiplicity of solutions to recognizing p53R175H with sufficient selectivity to mediate T cell killing of tumor but not normal cells.

β-Coronaviruses such as SARS-CoV-2 hijack coatomer protein-I (COPI) for spike protein retrograde trafficking to the progeny assembly site in endoplasmic reticulum-Golgi intermediate compartment (ERGIC). However, limited residue-level details are available into how the spike interacts with COPI. Here we identify an extended COPI binding motif in the spike that encompasses the canonical K-x-H dibasic sequence. This motif demonstrates selectivity for αCOPI subunit. Guided by an in silico analysis of dibasic motifs in the human proteome, we employ mutagenesis and binding assays to show that the spike motif terminal residues are critical modulators of complex dissociation, which is essential for spike release in ERGIC. αCOPI residues critical for spike motif binding are elucidated by mutagenesis and crystallography and found to be conserved in the zoonotic reservoirs, bats, pangolins, camels, and in humans. Collectively, our investigation on the spike motif identifies key COPI binding determinants with implications for retrograde trafficking.

β-Coronaviruses such as SARS-CoV-2 hijack coatomer protein-I (COPI) for spike protein retrograde trafficking to the progeny assembly site in endoplasmic reticulum-Golgi intermediate compartment (ERGIC). However, limited residue-level details are available into how the spike interacts with COPI. Here we identify an extended COPI binding motif in the spike that encompasses the canonical K-x-H dibasic sequence. This motif demonstrates selectivity for αCOPI subunit. Guided by an in silico analysis of dibasic motifs in the human proteome, we employ mutagenesis and binding assays to show that the spike motif terminal residues are critical modulators of complex dissociation, which is essential for spike release in ERGIC. αCOPI residues critical for spike motif binding are elucidated by mutagenesis and crystallography and found to be conserved in the zoonotic reservoirs, bats, pangolins, camels, and in humans. Collectively, our investigation on the spike motif identifies key COPI binding determinants with implications for retrograde trafficking.

T cells play a vital role in combatting SARS-CoV-2 and in forming long-term memory responses. Whereas extensive structural information is available on neutralizing antibodies against SARS-CoV-2, such information on SARS-CoV-2-specific T cell receptors (TCRs) bound to their peptide–MHC targets is lacking. We determined structures of a public and a private TCR from COVID-19 convalescent patients in complex with HLA-A2 and two SARS-CoV-2 spike protein epitopes (YLQ and RLQ). The structures revealed the basis for selection of particular TRAV and TRBV germline genes by the public but not the private TCR, and for the ability of both TCRs to recognize natural variants of YLQ and RLQ but not homologous epitopes from human seasonal coronaviruses. By elucidating the mechanism for TCR recognition of an immunodominant yet variable epitope (YLQ) and a conserved but less commonly targeted epitope (RLQ), this study can inform prospective efforts to design vaccines to elicit pan-coronavirus immunity.

T cells play a vital role in combatting SARS-CoV-2 and in forming long-term memory responses. Whereas extensive structural information is available on neutralizing antibodies against SARS-CoV-2, such information on SARS-CoV-2-specific T cell receptors (TCRs) bound to their peptide–MHC targets is lacking. We determined structures of a public and a private TCR from COVID-19 convalescent patients in complex with HLA-A2 and two SARS-CoV-2 spike protein epitopes (YLQ and RLQ). The structures revealed the basis for selection of particular TRAV and TRBV germline genes by the public but not the private TCR, and for the ability of both TCRs to recognize natural variants of YLQ and RLQ but not homologous epitopes from human seasonal coronaviruses. By elucidating the mechanism for TCR recognition of an immunodominant yet variable epitope (YLQ) and a conserved but less commonly targeted epitope (RLQ), this study can inform prospective efforts to design vaccines to elicit pan-coronavirus immunity.

Continuous outbreaks of highly pathogenic avian influenza (HPAI) viruses in commercial poultry have caused devastating losses to domestic poultry with a raising public health concern. The outbreaks of HPAI viruses have increased worldwide, including the North America. Therefore, vaccination has been considered as an alternative strategy for an efficient control of HPAI viruses. In this study, we aimed to generate Newcastle disease virus (NDV) vectored H7 serotype-specific vaccines by expressing the consensus sequence of the HA protein. Conventional NDV strain LaSota vector and a chimeric NDV vector containing the avian paramyxovirus type-2 F and HN protein were able to express the consensus sequence of HA protein. The protective efficacy of vaccines was evaluated in broiler chickens and in turkeys. One-day-old poults were prime immunized with the chimeric vector expressing the HA protein followed by boost immunization with LaSota vector expressing the HA protein or co-expressing the HA and NA proteins. Our vaccine candidates provided complete protection of broiler chickens from mortality and shedding of H7N8 HPAI challenge virus. Turkeys were better protected by boosting with the LaSota vector co-expressing the HA and NA proteins than the LaSota vector expressing only the HA protein. Our study demonstrated a potential use of heterologous prime and boost vaccination strategy to protect poultry against H7 HPAI viruses.

Genetic analyses of human type 1 diabetes (T1D) have yet to reveal a complete pathophysiologic mechanism. Inbred rats with a high-risk class II major histocompatibility complex (MHC) haplotype (RT1B/Du) can illuminate such mechanisms. Using T1D-susceptible LEW.1WR1 rats that express RT1B/Du and a susceptible allele of the Ubd promoter, we demonstrate that germline knockout of Tcrb-V13S1A1, which encodes the Vβ13a T cell receptor β chain, completely prevents diabetes. Using the RT1B/Du-identical LEW.1W rat, which does not develop T1D despite also having the same Tcrb-V13S1A1 β chain gene but a different allele at the Ubd locus, we show that knockout of the Ubash3a regulatory gene renders these resistant rats relatively susceptible to diabetes. In silico structural modeling of the susceptible allele of the Vβ13a TCR and its class II RT1u ligand suggests a mechanism by which a germline TCR β chain gene could promote susceptibility to T1D in the absence of downstream immunoregulation like that provided by UBASH3A. Together these data demonstrate the critical contribution of the Vβ13a TCR to the autoimmune synapse in T1D and the regulation of the response by UBASH3A. These experiments dissect the mechanisms by which MHC class II heterodimers, TCR and regulatory element interact to induce autoimmunity.