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Results for “major histocompatibility complex”

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33 records · Page 2

Multi-variate model of T cell clonotype competition and homeostasis

Abstract Diversity of the naive T cell repertoire is maintained by competition for stimuli provided by self-peptides bound to major histocompatibility complexes (self-pMHCs). We extend an existing bi-variate competition model to a multi-variate model of the dynamics of multiple T cell clonotypes which share stimuli. In order to understand the late-time behaviour of the system, we analyse: (i) the dynamics until the extinction of the first clonotype, (ii) the time to the first extinction event, (iii) the probability of extinction of each clonotype, and (iv) the size of the surviving clonotypes when the first extinction event takes place. We also find the probability distribution of the number of cell divisions per clonotype before its extinction. The mean size of a new clonotype at quasi-steady state is an increasing function of the stimulus available to it, and a decreasing function of the fraction of stimuli it shares with other clonotypes. Thus, the probability of, and time to, extinction of a new clonotype entering the pool of T cell clonotypes is determined by the extent of competition for stimuli it experiences and by its initial number of cells.

59 BASIC BIOLOGICAL SCIENCES↗

Differential roles of kinetic on- and off-rates in T-cell receptor signal integration revealed with a modified Fab’-DNA ligand

Antibody-derived T-cell receptor (TCR) agonists are commonly used to activate T cells. While antibodies can trigger TCRs regardless of clonotype, they bypass native T cell signal integration mechanisms that rely on monovalent, membrane-associated, and relatively weakly binding ligand in the context of cellular adhesion. Commonly used antibodies and their derivatives bind much more strongly than native peptide major histocompatibility complex (pMHC) ligands bind their cognate TCRs. Because ligand dwell time is a critical parameter that tightly correlates with physiological function of the TCR signaling system, there is a general need, both in research and therapeutics, for universal TCR ligands with controlled kinetic binding parameters. To this end, we have introduced point mutations into recombinantly expressed α-TCRβ H57 Fab to modulate the dwell time of monovalent Fab binding to TCR. When tethered to a supported lipid bilayer via DNA complementation, these monovalent Fab’-DNA ligands activate T cells with potencies well-correlated with their TCR binding dwell time. Single-molecule tracking studies in live T cells reveal that individual binding events between Fab'-DNA ligands and TCRs elicit local signaling responses closely resembling native pMHC. The unique combination of high on- and off-rates of the H57 R97L mutant enables direct observations of cooperative interplay between ligand binding and TCR-proximal condensation of the linker for activation of T cells, which is not readily visualized with pMHC. This work provides insights into how T cells integrate kinetic information from TCR ligands and introduces a method to develop affinity panels for polyclonal T cells, such as cells from a human patient.

Science & Technology - Other Topics↗

DeepNeo: a webserver for predicting immunogenic neoantigens

Abstract Non-self epitopes, whether originated from foreign substances or somatic mutations, trigger immune responses when presented by major histocompatibility complex (MHC) molecules and recognized by T cells. Identification of immunogenically active neoepitopes has significant implications in cancer and virus medicine. However, current methods are mostly limited to predicting physical binding of mutant peptides and MHCs. We previously developed a deep-learning based model, DeepNeo, to identify immunogenic neoepitopes by capturing the structural properties of peptide-MHC pairs with T cell reactivity. Here, we upgraded our DeepNeo model with up-to-date training data. The upgraded model (DeepNeo-v2) was improved in evaluation metrics and showed prediction score distribution that better fits known neoantigen behavior. The immunogenic neoantigen prediction can be conducted at https://deepneo.net.

Kim, Jeong Yeon↗

Biophysical and Structural Features of αβT ‐Cell Receptor Mechanosensing: A Paradigmatic Shift in Understanding T‐Cell Activation

ABSTRACT αβT cells protect vertebrates against many diseases, optimizing surveillance using mechanical force to distinguish between pathophysiologic cellular alterations and normal self‐constituents. The multi‐subunit αβT‐cell receptor (TCR) operates outside of thermal equilibrium, harvesting energy via physical forces generated by T‐cell motility and actin‐myosin machinery. When a peptide‐bound major histocompatibility complex molecule (pMHC) on an antigen presenting cell is ligated, the αβTCR on the T cell leverages force to form a catch bond, prolonging bond lifetime, and enhancing antigen discrimination. Under load, the αβTCR undergoes reversible structural transitions involving partial unfolding of its clonotypic immunoglobulin‐like (Ig) domains and coupled rearrangements of associated CD3 subunits and structural elements. We postulate that transitions provide critical energy to initiate the signaling cascade via induction of αβTCR quaternary structural rearrangements, associated membrane perturbations, exposure of CD3 ITAMs to phosphorylation by non‐receptor tyrosine kinases, and phase separation of signaling molecules. Understanding force‐mediated signaling by the αβTCR clarifies long‐standing questions regarding αβTCR antigen recognition, specificity and affinity, providing a basis for continued investigation. Future directions include examining atomistic mechanisms of αβTCR signal initiation, performance quality, tissue compliance adaptability, and T‐cell memory fate. The mechanotransduction paradigm will foster improved rational design of T‐cell based vaccines, CAR‐Ts, and adoptive therapies.

Immunology↗

Pre–T cell receptors topologically sample self-ligands during thymocyte β-selection

Self-discrimination, a critical but ill-defined molecular process programmed during thymocyte development, requires myriad pre–T cell receptors (preTCRs) and αβTCRs. Using x-ray crystallography, we show how a preTCR applies the concave β-sheet surface of its single variable domain (Vβ) to “horizontally” grab the protruding MHC α2-helix. By contrast, αβTCRs purpose all six complementarity-determining region (CDR) loops of their paired VαVβ module to recognize peptides bound to major histocompatibility complex molecules (pMHCs) in “vertical” head-to-head binding. Additionally, the preTCR topological fit ensures that CDR3β reaches the peptide’s featured C-terminal segment for pMHC sampling, establishing the subsequent αβTCR canonical docking mode. “Horizontal” docking precludes germline CDR1β- and CDR2β-MHC binding to broaden β-chain repertoire diversification before αβTCR-mediated selection refinement. Thus, one subunit successively attunes the recognition logic of related multicomponent receptors.

59 BASIC BIOLOGICAL SCIENCES↗

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4 + and CD8 + T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

60 APPLIED LIFE SCIENCES↗

Single-Cell Transcriptomic Analysis of Tumor-Derived Fibroblasts and Normal Tissue-Resident Fibroblasts Reveals Fibroblast Heterogeneity in Breast Cancer

Cancer-associated fibroblasts (CAFs) are a prominent stromal cell type in solid tumors and molecules secreted by CAFs play an important role in tumor progression and metastasis. CAFs coexist as heterogeneous populations with potentially different biological functions. Although CAFs are a major component of the breast cancer stroma, molecular and phenotypic heterogeneity of CAFs in breast cancer is poorly understood. In this study, we investigated CAF heterogeneity in triple-negative breast cancer (TNBC) using a syngeneic mouse model, BALB/c-derived 4T1 mammary tumors. Using single-cell RNA sequencing (scRNA-seq), we identified six CAF subpopulations in 4T1 tumors including: 1) myofibroblastic CAFs, enriched for α-smooth muscle actin and several other contractile proteins; 2) ‘inflammatory’ CAFs with elevated expression of inflammatory cytokines; and 3) a CAF subpopulation expressing major histocompatibility complex (MHC) class II proteins that are generally expressed in antigen-presenting cells. Comparison of 4T1-derived CAFs to CAFs from pancreatic cancer revealed that these three CAF subpopulations exist in both tumor types. Interestingly, cells with inflammatory and MHC class II-expressing CAF profiles were also detected in normal breast/pancreas tissue, suggesting that these phenotypes are not tumor microenvironment-induced. This work enhances our understanding of CAF heterogeneity, and specifically targeting these CAF subpopulations could be an effective therapeutic approach for treating highly aggressive TNBCs.

60 APPLIED LIFE SCIENCES↗

Ultrastructural Location and Interactions of the Immunoglobulin Receptor Binding Sequence within Fibrillar Type I Collagen

Collagen type I is a major constituent of animal bodies. It is found in large quantities in tendon, bone, skin, cartilage, blood vessels, bronchi, and the lung interstitium. It is also produced and accumulates in large amounts in response to certain inflammations such as lung fibrosis. Our understanding of the molecular organization of fibrillar collagen and cellular interaction motifs, such as those involved with immune-associated molecules, continues to be refined. In this study, antibodies raised against type I collagen were used to label intact D-periodic type I collagen fibrils and observed with atomic force microscopy (AFM), and X-ray diffraction (XRD) and immunolabeling positions were observed with both methods. The antibodies bind close to the C-terminal telopeptide which verifies the location and accessibility of both the major histocompatibility complex (MHC) class I (MHCI) binding domain and C-terminal telopeptide on the outside of the collagen fibril. The close proximity of the C-telopeptide and the MHC1 domain of type I collagen to fibronectin, discoidin domain receptor (DDR), and collagenase cleavage domains likely facilitate the interaction of ligands and receptors related to cellular immunity and the collagen-based Extracellular Matrix.

59 BASIC BIOLOGICAL SCIENCES↗

Class I and class II major histocompatibility molecules play a role in bone marrow-derived macrophage development

Class I and class II major histocompatibility complex (MHC) molecules play significant roles in T cell development and immune function. We show that MHCI- and MHCII-deficient mice have low numbers of macrophage precursors and circulating monocytes, as well as abnormal bone marrow cell colony-stimulating factor type 1 secretion and bone composition. We suggest that MHCI and MHCII molecules play a significant role in macrophage development.

Non-NASA Center↗

The HHV-6B U20 glycoprotein binds ULBP1, masking it from recognition by NKG2D and interfering with natural killer cell activation

Human Herpesvirus 6B (HHV-6B) impedes host immune responses by downregulating class I MHC molecules (MHC-I), hindering antigen presentation to CD8+ T cells. Downregulation of MHC-I disengages inhibitory receptors on natural killer (NK) cells, resulting in activation and killing of the target cell if NK cell activating receptors such as NKG2D have engaged stress ligands upregulated on the target cells. Previous work has shown that HHV-6B downregulates three MHC-like stress ligands MICB, ULBP1, and ULBP3, which are recognized by NKG2D. The U20 glycoprotein of the related virus HHV-6A has been implicated in the downregulation of ULBP1, but the precise mechanism remains undetermined. We set out to investigate the role of HHV-6B U20 in modulating NK cell activity. We used HHV-6B U20 expressed as a recombinant protein or transduced into target cells, as well as HHV-6B infection, to investigate binding interactions with NK cell ligands and receptors and to assess effects on NK cell activation. Small-angle X-ray scattering was used to align molecular models derived from machine-learning approaches. We demonstrate that U20 binds directly to ULBP1 with sub-micromolar affinity. Transduction of U20 decreases NKG2D binding to ULBP1 at the cell surface but does not decrease ULBP1 protein levels, either at the cell surface or in toto. HHV-6B infection and soluble U20 have the same effect. Transduction of U20 blocks NK cell activation in response to cell-surface ULBP1. Structural modeling of the U20 – ULBP1 complex indicates some similarities to the m152-RAE1γ complex.

60 APPLIED LIFE SCIENCES↗

Decreased non-MHC-restricted (CD56+) killer cell cytotoxicity after spaceflight

Cytotoxic activity of non-major histocompatibility complex-restricted (CD56+) (NMHC) killer cells and cell surface marker expression of peripheral blood mononuclear cells were determined before and after spaceflight. Ten astronauts (9 men, 1 woman) from two space shuttle missions (9- and 10-day duration) participated in the study. Blood samples were collected 10 days before launch, within 3 h after landing, and 3 days after landing. All peripheral blood mononuclear cell preparations were cryopreserved and analyzed simultaneously in a 4-h cytotoxicity (51)Cr release assay using K562 target cells. NMHC killer cell lytic activity was normalized per 1,000 CD56+ cells. When all 10 subjects were considered as one study group, NMHC killer cell numbers did not change significantly during the three sampling periods, but at landing lytic activity had decreased by approximately 40% (P < 0.05) from preflight values. Nine of ten astronauts had decreased lytic activity immediately after flight. NMHC killer cell cytotoxicity of only three astronauts returned toward preflight values by 3 days after landing. Consistent with decreased NMHC killer cell cytotoxicity, urinary cortisol significantly increased after landing compared with preflight levels. Plasma cortisol and ACTH levels at landing were not significantly different from preflight values. No correlation of changes in NMHC killer cell function or hormone levels with factors such as age, gender, mission, or spaceflight experience was found. After landing, expression of the major lymphocyte surface markers (CD3, CD4, CD8, CD14, CD16, CD56), as determined by flow cytometric analysis, did not show any consistent changes from measurements made before flight.

NASA Center JSC↗

Multivariate regression modelling for gender prediction using volatile organic compounds from hand odor profiles via HS-SPME-GC-MS

The efficacy of using human volatile organic compounds (VOCs) as a form of forensic evidence has been well demonstrated with canines for crime scene response, suspect identification, and location checking. Although the use of human scent evidence in the field is well established, the laboratory evaluation of human VOC profiles has been limited. This study used Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) to analyze human hand odor samples collected from 60 individuals (30 Females and 30 Males). The human volatiles collected from the palm surfaces of each subject were interpreted for classification and prediction of gender. The volatile organic compound (VOC) signatures from subjects’ hand odor profiles were evaluated with supervised dimensional reduction techniques: Partial Least Squares-Discriminant Analysis (PLS-DA), Orthogonal-Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Linear Discriminant Analysis (LDA). The PLS-DA 2D model demonstrated clustering amongst male and female subjects. The addition of a third component to the PLS-DA model revealed clustering and minimal separation of male and female subjects in the 3D PLS-DA model. The OPLS-DA model displayed discrimination and clustering amongst gender groups with leave one out cross validation (LOOCV) and 95% confidence regions surrounding clustered groups without overlap. The LDA had a 96.67% accuracy rate for female and male subjects. The culminating knowledge establishes a working model for the prediction of donor class characteristics using human scent hand odor profiles.

59 BASIC BIOLOGICAL SCIENCES↗

Chronic N(G)-nitro-L-arginine methyl ester-induced hypertension : novel molecular adaptation to systolic load in absence of hypertrophy

BACKGROUND: Chronic N(G)-nitro-L-arginine methyl ester (L-NAME), which inhibits nitric oxide synthesis, causes hypertension and would therefore be expected to induce robust cardiac hypertrophy. However, L-NAME has negative metabolic effects on protein synthesis that suppress the increase in left ventricular (LV) mass in response to sustained pressure overload. In the present study, we used L-NAME-induced hypertension to test the hypothesis that adaptation to pressure overload occurs even when hypertrophy is suppressed. METHODS AND RESULTS: Male rats received L-NAME (50 mg. kg(-1). d(-1)) or no drug for 6 weeks. Rats with L-NAME-induced hypertension had levels of systolic wall stress similar to those of rats with aortic stenosis (85+/-19 versus 92+/-16 kdyne/cm). Rats with aortic stenosis developed a nearly 2-fold increase in LV mass compared with controls. In contrast, in the L-NAME rats, no increase in LV mass (1. 00+/-0.03 versus 1.04+/-0.04 g) or hypertrophy of isolated myocytes occurred (3586+/-129 versus 3756+/-135 microm(2)) compared with controls. Nevertheless, chronic pressure overload was not accompanied by the development of heart failure. LV systolic performance was maintained by mechanisms of concentric remodeling (decrease of in vivo LV chamber dimension relative to wall thickness) and augmented myocardial calcium-dependent contractile reserve associated with preserved expression of alpha- and beta-myosin heavy chain isoforms and sarcoplasmic reticulum Ca(2+) ATPase (SERCA-2). CONCLUSIONS: When the expected compensatory hypertrophic response is suppressed during L-NAME-induced hypertension, severe chronic pressure overload is associated with a successful adaptation to maintain systolic performance; this adaptation depends on both LV remodeling and enhanced contractility in response to calcium.

Non-NASA Center↗

Comparative Analysis of TCR and TCR-pMHC Complex Structure Prediction Tools

The rapid development of computational approaches for predicting the structures of T cell receptors (TCRs) and TCR-peptide-major histocompatibility (TCR-pMHC) complexes, accelerated by AI breakthroughs such as AlphaFold, has made it feasible to calculate these structures with increasing accuracy. Although these tools show great potential, their relative accuracy and limitations remain unclear due to the lack of standardized benchmarks. Here, we systematically evaluate seven tools for predicting isolated TCR structures together with six tools for predicting TCR-pMHC complex structures. The methods include homology-based approaches, general prediction tools using AlphaFold, TCR-specific tools derived from AlphaFold2, and the newly developed tFold-TCR model. The evaluation uses a post-training data set comprising 40 αβ TCRs and 27 TCR-pMHC complexes (21 Class I and 6 Class II). Model accuracy is assessed at global, local, and interface levels using a variety of metrics. We find that each tool offers distinct advantages in various aspects of its predictions. AlphaFold2, AlphaFold3, and tFold-TCR excel in overall accuracy of TCR structure prediction, and TCRmodel2 and AlphaFold2 perform well in overall accuracy of TCR-pMHC structure prediction. However, TCR-specific tools derived from AlphaFold2 show lower accuracy in the framework region than both homology-based methods and general-purpose tools such as AlphaFold, and challenges remain for all in modeling CDR3 loops, docking orientations, TCR-peptide interfaces, and Class II MHC-peptide interfaces. Furthermore, these findings will guide researchers in selecting appropriate tools, emphasize the importance of using multiple evaluation metrics to assess model performance, and offer suggestions for improving TCR and TCR-pMHC structure prediction tools.

Chemical structure↗

Complex high affinity interactions occur between MHCI and superantigens

Staphylococcal enterotoxins A and C1 (SEA or SEC1) bound to major histocompatibility-I (MHCI) molecules with high affinity (binding constants ranging from 1.1 microM to 79 nM). SEA and SEC1 directly bound MHCI molecules that had been captured by monoclonal antibodies specific for H-2Kk, H-2Dk, or both. In addition, MHCI-specific antibodies inhibited the binding of SEC1 to LM929 cells and SEA competitively inhibited SEC1 binding; indicating that the superantigens bound to MHCI on the cell surface. The affinity and number of superantigen binding sites differed depending on whether MHCI was expressed in the membrane of LM929 cells or whether it was captured. These data support the hypothesis that MHCI molecules can serve as superantigen receptors.

NASA Discipline Cell Biology↗