Genomic composition and pathomechanisms of porcine circoviruses: A review
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Gao, Yong-Yu [College of Animal Medicine, Jilin Ag↗
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Results for “ANTIGENS”
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Targeting a proteolytic neoepitope on CUB domain containing protein 1 ( CDCP1 ) for RAS -driven cancers
Extracellular proteolysis is frequently dysregulated in disease and can generate proteoforms with unique neoepitopes not found in healthy tissue. Here, we demonstrate that Abs that selectively recognize a proteolytic neoepitope on CUB domain containing protein 1 (CDCP1) could enable more effective and safer treatments for solid tumors. CDCP1 is highly overexpressed in RAS-driven cancers, and its ectodomain is cleaved by extracellular proteases. Biochemical, biophysical, and structural characterization revealed that the 2 cleaved fragments of CDCP1 remain tightly associated with minimal proteolysis-induced conformational change. Using differential phage display, we generated recombinant Abs that are exquisitely selective to cleaved CDCP1 with no detectable binding to the uncleaved form. These Abs potently targeted cleaved CDCP1-expressing cancer cells as an Ab-drug conjugate, an Ab-radionuclide conjugate, and a bispecific T cell engager. In a syngeneic pancreatic tumor model, these cleaved-specific Abs showed tumor-specific localization and antitumor activity with superior safety profiles compared with a pan-CDCP1 approach. Targeting proteolytic neoepitopes could provide an orthogonal "AND" gate for improving the therapeutic index.
59 BASIC BIOLOGICAL SCIENCES↗
HLA-Clus: HLA class I clustering based on 3D structure
In a previous paper, we classified populated HLA class I alleles into supertypes and subtypes based on the similarity of 3D landscape of peptide binding grooves, using newly defined structure distance metric and hierarchical clustering approach. Compared to other approaches, our method achieves higher correlation with peptide binding specificity, intra-cluster similarity (cohesion), and robustness. Here we introduce HLA-Clus, a Python package for clustering HLA Class I alleles using the method we developed recently and describe additional features including a new nearest neighbor clustering method that facilitates clustering based on user-defined criteria. The HLA-Clus pipeline includes three stages: First, HLA Class I structural models are coarse grained and transformed into clouds of labeled points. Second, similarities between alleles are determined using a newly defined structure distance metric that accounts for spatial and physicochemical similarities. Finally, alleles are clustered via hierarchical or nearest-neighbor approaches. We also interfaced HLA-Clus with the peptide:HLA affinity predictor MHCnuggets. By using the nearest neighbor clustering method to select optimal allele-specific deep learning models in MHCnuggets, the average accuracy of peptide binding prediction of rare alleles was improved. The HLA-Clus package offers a solution for characterizing the peptide binding specificities of a large number of HLA alleles. This method can be applied in HLA functional studies, such as the development of peptide affinity predictors, disease association studies, and HLA matching for grafting. HLA-Clus is freely available at our GitHub repository (https://github.com/yshen25/HLA-Clus).
59 BASIC BIOLOGICAL SCIENCES↗
Mapping the immunogenic landscape of near-native HIV-1 envelope trimers in non-human primates
The induction of broad and potent immunity by vaccines is the key focus of research efforts aimed at protecting against HIV-1 infection. Soluble native-like HIV-1 envelope glycoproteins have shown promise as vaccine candidates as they can induce potent autologous neutralizing responses in rabbits and non-human primates. In this study, monoclonal antibodies were isolated and characterized from rhesus macaques immunized with the BG505 SOSIP.664 trimer to better understand vaccine-induced antibody responses. Our studies reveal a diverse landscape of antibodies recognizing immunodominant strain-specific epitopes and non-neutralizing neo-epitopes. Additionally, we isolated a subset of mAbs against an epitope cluster at the gp120-gp41 interface that recognize the highly conserved fusion peptide and the glycan at position 88 and have characteristics akin to several human-derived broadly neutralizing antibodies.
59 BASIC BIOLOGICAL SCIENCES↗
Effects of HLA single chain trimer design on peptide presentation and stability
MHC class I “single-chain trimer” molecules, coupling MHC heavy chain, β 2 -microglobulin, and a specific peptide into a single polypeptide chain, are widely used in research. To more fully understand caveats associated with this design that may affect its use for basic and translational studies, we evaluated a set of engineered single-chain trimers with combinations of stabilizing mutations across eight different classical and non-classical human class I alleles with 44 different peptides, including a novel human/murine chimeric design. While, overall, single-chain trimers accurately recapitulate native molecules, care was needed in selecting designs for studying peptides longer or shorter than 9-mers, as single-chain trimer design could affect peptide conformation. In the process, we observed that predictions of peptide binding were often discordant with experiment and that yields and stabilities varied widely with construct design. We also developed novel reagents to improve the crystallizability of these proteins and confirmed novel modes of peptide presentation.
59 BASIC BIOLOGICAL SCIENCES↗
TCR-H: explainable machine learning prediction of T-cell receptor epitope binding on unseen datasets
Artificial-intelligence and machine-learning (AI/ML) approaches to predicting T-cell receptor (TCR)-epitope specificity achieve high performance metrics on test datasets which include sequences that are also part of the training set but fail to generalize to test sets consisting of epitopes and TCRs that are absent from the training set, i.e., are ‘unseen’ during training of the ML model. We present TCR-H, a supervised classification Support Vector Machines model using physicochemical features trained on the largest dataset available to date using only experimentally validated non-binders as negative datapoints. TCR-H exhibits an area under the curve of the receiver-operator characteristic (AUC of ROC) of 0.87 for epitope ‘hard splitting’ (i.e., on test sets with all epitopes unseen during ML training), 0.92 for TCR hard splitting and 0.89 for ‘strict splitting’ in which neither the epitopes nor the TCRs in the test set are seen in the training data. Furthermore, we employ the SHAP (Shapley additive explanations) eXplainable AI (XAI) method for post hoc interrogation to interpret the models trained with different hard splits, shedding light on the key physiochemical features driving model predictions. TCR-H thus represents a significant step towards general applicability and explainability of epitope:TCR specificity prediction.
60 APPLIED LIFE SCIENCES↗
Vaccine Advances against Venezuelan, Eastern, and Western Equine Encephalitis Viruses
Vaccinations are a crucial intervention in combating infectious diseases. The three neurotropic Alphaviruses, Eastern (EEEV), Venezuelan (VEEV), and Western (WEEV) equine encephalitis viruses, are pathogens of interest for animal health, public health, and biological defense. In both equines and humans, these viruses can cause febrile illness that may progress to encephalitis. Currently, there are no licensed treatments or vaccines available for these viruses in humans. Experimental vaccines have shown variable efficacy and may cause severe adverse effects. Here, we outline recent strategies used to generate vaccines against EEEV, VEEV, and WEEV with an emphasis on virus-vectored and plasmid DNA delivery. Despite candidate vaccines protecting against one of the three viruses, few studies have demonstrated an effective trivalent vaccine. We evaluated the potential of published vaccines to generate cross-reactive protective responses by comparing DNA vaccine sequences to a set of EEEV, VEEV, and WEEV genomes and determining the vaccine coverages of potential epitopes. Finally, we discuss future directions in the development of vaccines to combat EEEV, VEEV, and WEEV.
59 BASIC BIOLOGICAL SCIENCES↗