Cell Receptor Interactions Research Articles

Integration of kinetic data into affinity-based models for improved T cell specificity prediction

T cell receptor (TCR) and peptide-major histocompatibility complex (pMHC) interactions that result in T cell activation are complex and have been distinguished by their equilibrium affinity and kinetic profiles. While prior affinity-based models can successfully predict meaningful TCR-pMHC interactions in many cases, they occasionally fail at identifying TCR-pMHC interactions with low binding affinity. This study analyzes TCR-pMHC systems for which empirical kinetic and affinity data exist and prior affinity-based predictions have failed. We identify criteria for TCR-pMHC systems with available kinetic information where the introduction of a correction factor improves energy-based model predictions. This kinetic correction factor offers a means to refine existing models with additional data and offers molecular insights to help reconcile previously conflicting reports concerning the influence of TCR-pMHC binding kinetics and affinity on T cell activation.

Advanced Quantification of Receptor-Ligand Interaction Lifetimes via Single-Molecule FRET Microscopy.

Receptor-ligand interactions at cell interfaces initiate signaling cascades essential for cellular communication and effector functions. Specifically, T cell receptor (TCR) interactions with pathogen-derived peptides presented by the major histocompatibility complex (pMHC) molecules on antigen-presenting cells are crucial for T cell activation. The binding duration, or dwell time, of TCR-pMHC interactions correlates with downstream signaling efficacy, with strong agonists exhibiting longer lifetimes compared to weak agonists. Traditional surface plasmon resonance (SPR) methods quantify 3D affinity but lack cellular context and fail to account for factors like membrane fluctuations. In the recent years, single-molecule Förster resonance energy transfer (smFRET) has been applied to measure 2D binding kinetics of TCR-pMHC interactions in a cellular context. Here, we introduce a rigorous mathematical model based on survival analysis to determine exponentially distributed receptor-ligand interaction lifetimes, verified through simulated data. Additionally, we developed a comprehensive analysis pipeline to extract interaction lifetimes from raw microscopy images, demonstrating the model's accuracy and robustness across multiple TCR-pMHC pairs. Our new software suite automates data processing to enhance throughput and reduce bias. This methodology provides a refined tool for investigating T cell activation mechanisms, offering insights into immune response modulation.

Parainfluenza Virus 5 V Protein Blocks Interferon Gamma-Mediated Upregulation of NK Cell Inhibitory Ligands and Improves NK Cell Killing of Neuroblastoma Cells.

Natural killer (NK) cells can be effective immunotherapeutic anti-cancer agents due to their ability to selectively target and kill tumor cells. This activity is modulated by the interaction of NK cell receptors with inhibitory ligands on the surface of target cells. NK cell inhibitory ligands can be upregulated on tumor cell surfaces in response to interferon-gamma (IFN-γ), a cytokine which is produced by activated NK cells. We hypothesized that the resistance of tumor cells to NK cell killing could be overcome by expression of the parainfluenza virus 5 (PIV5) V protein, which has known roles in blocking IFN-γ signaling. This was tested with human PM21-NK cells produced through a previously developed particle-based method which yields superior NK cells for immunotherapeutic applications. Infection of human SK-N-SH neuroblastoma cells with PIV5 blocked IFN-γ-mediated upregulation of three NK cell inhibitory ligands and enhanced in vitro killing of these tumor cells by PM21-NK cells. SK-N-SH cells transduced to constitutively express the V protein alone were resistant to IFN-γ-mediated increases in cell surface expression of NK cell inhibitory ligands. Real-time in vitro cell viability assays demonstrated that V protein expression in SK-N-SH cells was sufficient to increase PM21-NK cell-mediated killing. Toward a potential therapeutic application, transient lentiviral delivery of the V gene also enhanced PM21-NK cell killing in vitro. Our results provide the foundation for novel therapeutic applications of V protein expression in combination with ex vivo NK cell therapy to effectively increase the killing of tumor cells.

Self-assembling Peptides Based Fibers: A Pioneering Innovation for Regenerative Medicine

Self-assembling peptides (SAPs) have emerged as a groundbreaking platform in regenerative medicine, offering innovative strategies for tissue engineering and repair. These biomolecules, designed to autonomously organize into nanofibers, mimic the natural extracellular matrix, providing essential structural support and biological cues for tissue regeneration. This review highlights the versatile applications of SAPs in regenerating diverse tissues, including bone, cartilage, cardiac, neural, and dermal structures, showcasing their potential to address a broad spectrum of medical challenges. The unique properties of SAPs, such as biocompatibility, biodegradability and specific cell receptor interaction capabilities, make them ideal for developing advanced therapeutic strategies. We discuss here the molecular design principles that allow for precise control over the nanofibers physical and chemical characteristics, facilitating the creation of scaffolds that promote cell attachment, proliferation, and differentiation. Additionally, the review covers the use of SAPs in drug delivery systems, emphasizing their ability to control the release of therapeutic agents, a critical aspect in enhancing tissue repair processes. Moreover, we address key considerations regarding the safety, biodegradability and potential immunogenicity of SAPs, underscoring the importance of thorough preclinical and clinical evaluations. The future directions and challenges in optimizing SAPs design and functionalization for maximizing regenerative outcomes are also explored.

Cognate antigen-independent differentiation of resident memory T cells in chronic kidney disease.

Resident memory T cells (TRMs), which are memory T cells that are retained locally within tissues, have recently been described as antigen-specific frontline defenders against pathogens in barrier and nonbarrier epithelial tissues. They have also been noted for perpetuating chronic inflammation. The conditions responsible for TRM differentiation are still poorly understood, and their contributions, if any, to sterile models of chronic kidney disease (CKD) remain a mystery. In this study, we subjected male C57BL/6J mice and OT-1 transgenic mice to five consecutive days of 2 mg/kg aristolochic acid (AA) injections intraperitoneally to induce CKD or saline injections as a control. We evaluated their kidney immune profiles at 2 wk, 6 wk, and 6 mo after treatment. We identified a substantial population of TRMs in the kidneys of mice with AA-induced CKD. Flow cytometry of injured kidneys showed T cells bearing TRM surface markers and single-cell (sc) RNA sequencing revealed these cells as expressing well-known TRM transcription factors and receptors responsible for TRM differentiation and maintenance. Although kidney TRMs expressed Cd44, a marker of antigen experience and T cell activation, their derivation was independent of cognate antigen-T cell receptor interactions, as the kidneys of transgenic OT-1 mice still harbored considerable proportions of TRMs after injury. Our results suggest a nonantigen-specific or antigen-independent mechanism capable of generating TRMs in the kidney and highlight the need to better understand TRMs and their involvement in CKD.NEW & NOTEWORTHY Resident memory T cells (TRMs) differentiate and are retained within the kidneys of mice with aristolochic acid (AA)-induced chronic kidney disease (CKD). Here, we characterized this kidney TRM population and demonstrated TRM derivation in the kidneys of OT-1 transgenic mice with AA-induced CKD. A better understanding of TRMs and the processes by which they can differentiate independent of antigen may help our understanding of the interactions between the immune system and kidneys.

HLA-DPB1*13:01 associates with enhanced, and KIR2DS4*001 with diminished protection from developing severe COVID-19.

Extreme polymorphism of HLA and killer-cell immunoglobulin-like receptors (KIR) differentiates immune responses across individuals. Additional to T cell receptor interactions, subsets of HLA class I act as ligands for inhibitory and activating KIR, allowing natural killer (NK) cells to detect and kill infected cells. We investigated the impact of HLA and KIR polymorphism on the severity of COVID-19. High resolution HLA class I and II and KIR genotypes were determined from 403 non-hospitalized and 1575 hospitalized SARS-CoV-2 infected patients from Italy collected in 2020. We observed that possession of the activating KIR2DS4*001 allotype is associated with severe disease, requiring hospitalization (OR = 1.48, 95% CI 1.20-1.85, pc = 0.017), and this effect is greater in individuals homozygous for KIR2DS4*001 (OR = 3.74, 95% CI 1.75-9.29, pc = 0.003). We also observed the HLA class II allotype, HLA-DPB1*13:01 protects SARS-CoV-2 infected patients from severe disease (OR = 0.49, 95% CI 0.33-0.74, pc = 0.019). These association analyses were replicated using logistic regression with sex and age as covariates. Autoantibodies against IFN-α associated with COVID-19 severity were detected in 26% of 156 hospitalized patients tested. HLA-C*08:02 was more frequent in patients with IFN-α autoantibodies than those without, and KIR3DL1*01502 was only present in patients lacking IFN-α antibodies. These findings suggest that KIR and HLA polymorphism is integral in determining the clinical outcome following SARS-CoV-2 infection, by influencing the course both of innate and adaptive immunity.

Defining and Studying B Cell Receptor and TCR Interactions.

BCRs (Abs) and TCRs (or adaptive immune receptors [AIRs]) are the means by which the adaptive immune system recognizes foreign and self-antigens, playing an integral part in host defense, as well as the emergence of autoimmunity. Importantly, the interaction between AIRs and their cognate Ags defies a simple key-in-lock paradigm and is instead a complex many-to-many mapping between an individual's massively diverse AIR repertoire, and a similarly diverse antigenic space. Understanding how adaptive immunity balances specificity with epitopic coverage is a key challenge for the field, and terms such as broad specificity, cross-reactivity, and polyreactivity remain ill-defined and are used inconsistently. In this Immunology Notes and Resources article, a group of experimental, structural, and computational immunologists define commonly used terms associated with AIR binding, describe methodologies to study these binding modes, as well as highlight the implications of these different binding modes for therapeutic design.

Shexiang Tongxin Dropping Pill Allieviates Heart Failure via Extracellula Matrix-Receptor Interaction Pathways Based on RNA-Seq Transcriptomics and Experimental Studies.

To investigate the protective mechanisms of Chinese medicine Shexiang Tongxin Dropping Pills (STDP) on heart failure (HF). Isoproterenol (ISO)-induced HF rat model and angiotensin II (Ang II)-induced neonatal rat cardiac fibroblast (CFs) model were used in the present study. HF rats were treated with and without STDP (3 g/kg). RNA-seq was performed to identify differentially expressed genes (DEGs). Cardiac function was evaluated by echocardiography. Hematoxylin and eosin and Masson's stainings were taken to assess cardiac fibrosis. The levels of collagen I (Col I) and collagen III (Col III) were detected by immunohistochemical staining. CCK8 kit and transwell assay were implemented to test the CFs' proliferative and migratory activity, respectively. The protein expressions of α-smooth muscle actin (α-SMA), matrix metalloproteinase-2 (MMP-2), MMP-9, Col I, and Col III were detected by Western blotting. The results of RNA-seq analysis showed that STDP exerted its pharmacological effects on HF via multiple signaling pathways, such as the extracellular matrix (ECM)-receptor interaction, cell cycle, and B cell receptor interaction. Results from in vivo experiments demonstrated that STDP treatment reversed declines in cardiac function, inhibiting myocardial fibrosis, and reversing increases in Col I and Col III expression levels in the hearts of HF rats. Moreover, STDP (6, 9 mg/mL) inhibited the proliferation and migration of CFs exposed to Ang II in vitro (P<0.05). The activation of collagen synthesis and myofibroblast generation were markedly suppressed by STDP, also the synthesis of MMP-2 and MMP-9, as well as ECM components Col I, Col III, and α-SMA were decreased in Ang II-induced neonatal rats' CFs. STDP had anti-fibrotic effects in HF, which might be caused by the modulation of ECM-receptor interaction pathways. Through the management of cardiac fibrosis, STDP may be a compelling candidate for improving prognosis of HF.

Natural selection differences detected in key protein domains between non-pathogenic and pathogenic feline coronavirus phenotypes.

Feline coronaviruses (FCoVs) commonly cause mild enteric infections in felines worldwide (termed feline enteric coronavirus [FECV]), with around 12 per cent developing into deadly feline infectious peritonitis (FIP; feline infectious peritonitis virus [FIPV]). Genomic differences between FECV and FIPV have been reported, yet the putative genotypic basis of the highly pathogenic phenotype remains unclear. Here, we used state-of-the-art molecular evolutionary genetic statistical techniques to identify and compare differences in natural selection pressure between FECV and FIPV sequences, as well as to identify FIPV- and FECV-specific signals of positive selection. We analyzed full-length FCoV protein coding genes thought to contain mutations associated with FIPV (Spike, ORF3abc, and ORF7ab). We identified two sites exhibiting differences in natural selection pressure between FECV and FIPV: one within the S1/S2 furin cleavage site (FCS) and the other within the fusion domain of Spike. We also found fifteen sites subject to positive selection associated with FIPV within Spike, eleven of which have not previously been suggested as possibly relevant to FIP development. These sites fall within Spike protein subdomains that participate in host cell receptor interaction, immune evasion, tropism shifts, host cellular entry, and viral escape. There were fourteen sites (twelve novel sites) within Spike under positive selection associated with the FECV phenotype, almost exclusively within the S1/S2 FCS and adjacent to C domain, along with a signal of relaxed selection in FIPV relative to FECV, suggesting that furin cleavage functionality may not be needed for FIPV. Positive selection inferred in ORF7b was associated with the FECV phenotype and included twenty-four positively selected sites, while ORF7b had signals of relaxed selection in FIPV. We found evidence of positive selection in ORF3c in FCoV-wide analyses, but no specific association with the FIPV or FECV phenotype. We hypothesize that some combination of mutations in FECV may contribute to FIP development, and that it is unlikely to be one singular 'switch' mutational event. This work expands our understanding of the complexities of FIP development and provides insights into how evolutionary forces may alter pathogenesis in coronavirus genomes.

Interactions between Gender and Sepsis-Implications for the Future.

Sex and gender dimorphisms are found in a large variety of diseases, including sepsis and septic shock which are more prevalent in men than in women. Animal models show that the host response to pathogens differs in females and males. This difference is partially explained by sex polarization of the intracellular pathways responding to pathogen-cell receptor interactions. Sex hormones seem to be responsible for this polarization, although other factors, such as chromosomal effects, have yet to be investigated. In brief, females are less susceptible to sepsis and seem to recover more effectively than males. Clinical observations produce more nuanced findings, but men consistently have a higher incidence of sepsis, and some reports also claim higher mortality rates. However, variables other than hormonal differences complicate the interaction between sex and sepsis, including comorbidities as well as social and cultural differences between men and women. Conflicting data have also been reported regarding sepsis-attributable mortality rates among pregnant women, compared with non-pregnant females. We believe that unraveling sex differences in the host response to sepsis and its treatment could be the first step in personalized, phenotype-based management of patients with sepsis and septic shock.

BULK RNA-SEQUENCING OF BLOOD INFORMS MOLECULAR DIAGNOSES IN VERY EARLY ONSET INFLAMMATORY BOWEL DISEASE

Abstract BACKGROUND Very early onset inflammatory bowel disease (VEOIBD) is defined as disease onset prior to age 6. VEOIBD is monogenic in &amp;gt;5% of cases; however, in the remaining cases, molecular basis of disease is unknown. We aimed to utilize bulk RNA-seq of blood to 1) define transcriptional signatures in established monogenic IBD and 2) to inform novel molecular diagnoses. METHODS We sequenced the transcriptomes of 115 whole blood samples, comprising patients with VEOIBD of a known monogenic cause (n=35), VEOIBD without a known monogenic cause (n=70), and healthy controls (n=10). We focused on genes whose normalized expression was at least 5 standard deviations away from the population mean in at least one sample. We comprehensively characterized clinical phenotypes, to assess concordance with known pathway and gene function, and compared to whole exome sequencing data where available. We interrogated Bayesian IBD networks to assess for enrichment of genes of interest. RESULTS First, we report on a novel transcriptional signature shared by two patients with VEOIBD secondary to X-linked agammaglobulinemia (pathogenic BTK mutations). The signature is defined by under-expression of CXCR5 and FCRL5 (Fig 1) and suggests reduced transcripts secondary to B-cell depletion or novel BTK-dependent mechanisms of gene transcription. Second, we report on three novel candidate VEOIBD genes identified through our approach: MSN, SLC39A4, and BTN3A2 (Fig 2). MSN expression was below threshold in one patient with VEOIBD complicated by fistulae, recurrent infections, and death from pneumonia at age 62. Review of his exome revealed a novel loss of function mutation in MSN. MSN encodes moesin, an actin cytoskeleton modulator, which regulates lymphocyte migration and adhesion. Mutations in MSN are associated with X-linked moesin-associated immunodeficiency, which was first reported in a patient with IBD this year. SLC39A4, which encodes an intestinal zinc transporter, was below threshold in two patients. Mutations in SLC39A4 are associated with acrodermatitis enteropathica, characterized by dermatitis and diarrhea. One patient has VEOIBD with dermatitis; the second has VEOIBD complicated by toxic megacolon and colectomy. Coding mutations in SLC39A4 have not been identified. Further molecular assessment of zinc transporter function is underway. Lastly, BTN3A2 expression was below threshold in two patients with infantile-onset IBD. BTN3A2 plays a role in T cell receptor interactions and NF-KB signaling. Bayesian IBD networks, built from independent cohorts, revealed BTN3A2 and SLC39A4 subnetworks to be enriched in predicted key driver genes of inflammation, further supporting these genes’ potential disease association. CONCLUSIONS Bulk RNA-seq in blood can be used as a diagnostic tool to aid in identifying novel molecular pathways and monogenic diagnoses in VEOIBD.

Delayed Drug Hypersensitivity Reactions: Molecular Recognition, Genetic Susceptibility, and Immune Mediators.

Drug hypersensitivity reactions are classified into immediate and delayed types, according to the onset time. In contrast to the immediate type, delayed drug hypersensitivity mainly involves T lymphocyte recognition of the drug antigens and cell activation. The clinical presentations of such hypersensitivity are various and range from mild reactions (e.g., maculopapular exanthema (MPE) and fixed drug eruption (FDE)), to drug-induced liver injury (DILI) and severe cutaneous adverse reactions (SCARs) (e.g., Stevens-Johnson syndrome (SJS), toxic epidermal necrolysis (TEN), drug reaction with eosinophilia and systemic symptoms (DRESS), and acute generalized exanthematous pustulosis (AGEP)). The common culprits of delayed drug hypersensitivity include anti-epileptics, antibiotics, anti-gout agents, anti-viral drugs, etc. Delayed drug hypersensitivity is proposed to be initiated by different models of molecular recognition, composed of drug/metabolite antigen and endogenous peptide, HLA presentation, and T cell receptor (TCR) interaction. Increasing the genetic variants of HLA loci and drug metabolic enzymes has been identified to be responsible for delayed drug hypersensitivity. Furthermore, preferential TCR clonotypes, and the activation of cytotoxic proteins/cytokines/chemokines, are also involved in the pathogenesis of delayed drug hypersensitivity. This review provides a summary of the current understanding of the molecular recognition, genetic susceptibility, and immune mediators of delayed drug hypersensitivity.

Identification of Smoking-Associated Transcriptome Aberration in Blood with Machine Learning Methods.

Long-term cigarette smoking causes various human diseases, including respiratory disease, cancer, and gastrointestinal (GI) disorders. Alterations in gene expression and variable splicing processes induced by smoking are associated with the development of diseases. This study applied advanced machine learning methods to identify the isoforms with important roles in distinguishing smokers from former smokers based on the expression profile of isoforms from current and former smokers collected in one previous study. These isoforms were deemed as features, which were first analyzed by the Boruta to select features highly correlated with the target variables. Then, the selected features were evaluated by four feature ranking algorithms, resulting in four feature lists. The incremental feature selection method was applied to each list for obtaining the optimal feature subsets and building high-performance classification models. Furthermore, a series of classification rules were accessed by decision tree with the highest performance. Eventually, the rationality of the mined isoforms (features) and classification rules was verified by reviewing previous research. Features such as isoforms ENST00000464835 (expressed by LRRN3), ENST00000622663 (expressed by SASH1), and ENST00000284311 (expressed by GPR15), and pathways (cytotoxicity mediated by natural killer cell and cytokine-cytokine receptor interaction) revealed by the enrichment analysis, were highly relevant to smoking response, suggesting the robustness of our analysis pipeline.

Targeting SARS-CoV-2 and host cell receptor interactions

Despite the availability of vaccines and therapeutics, continual genetic alterations render the severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) a persistent threat, particularly for the immunocompromised and elderly. Through interactions of its spike (S) protein with different receptors and coreceptors on host cell surfaces, the virus enters the cell either via fusion with the plasma membrane or through endocytosis. Angiotensin-converting enzyme 2 (ACE2) has been identified as a key receptor utilized by SARS-CoV-2 and related human coronaviruses to mediate cell entry in the lung airways. Auxiliary SARS-CoV-2 entry receptors such as ASGPR1, Kremen protein 1, integrins have also been reported. In this review, therapeutic approaches to block SARS-CoV-2 and host cell receptor interactions are discussed.

Optimized Purification of CIDRα-PfEMP1 Plasmodium falciparum Recombinant Protein with Affinity Chromatography

Interaction of Cysteine-rich Interdomain Region (CIDR)α-Plasmodium falciparum Erythrocyte Membrane Protein (PfEMP1) and Endothelial Cell Receptors especially CD36 on host cells is main malaria pathogenesis, makes this domain as a malaria vaccine candidate. Recently, the development of the malaria vaccine is conducted by recombinant technology, and the purification of the CIDRα-PfEMP1 recombinant protein is a pivotal step. This study aimed to determine an optimal condition to purify the CIDRα-PfEMP1 recombinant protein by affinity chromatography through imidazole and NaCl concentration. The purified recombinant protein was visualized using SDS-PAGE and its concentration was measured using Image J software and Bradford Assay. The data were analyzed using SPSS 26 software, and the Paired T-Test analysis was conducted to compare the concentration of purified recombinant protein from two different methods. The result showed that thetarget band of purified recombinant protein was 27 kDa. The thickest target protein band was observed in purified recombinant protein using 140 mM imidazole and 300 mM NaCl. The recombinant protein concentration using Image J software was 0.025 µg/µL, while the Bradford Assay was 0.56 µg/µL. The Paired T-Test analysis has a significance value of 0.010 (p&lt;0.05), meaning there was a significant difference between the concentration measurement using Image J software and Bradford Assay. In conclusion, the optimized condition to purify the CIDRα-PfEMP1 recombinant protein by affinity chromatography was using 140 mM imidazole and 300 mM NaCl. It is suggested to measure the purified CIDRα-PfEMP1 recombinant protein concentration using the Bradford Assay method due to its convenience and sensitivity.

P389: BISPECIFIC ANTIBODIES ACTIVATE AUTOLOGOUS LEUKEMIA-REACTIVE T CELLS IN ACUTE MYELOID LEUKEMIA

Background: Acute myeloid leukemia (AML) is a highly immunosuppressive disease with a high risk of relapse. This makes the finding of effective immunotherapy-based treatments important, but also difficult. T cell-engaging bispecific antibodies (TCEs) are designed to bind to both T cells and target cells, activate the T cells and thus induce an immune response against the leukemia cells without employing the MHC-T cell receptor (TCR) interaction. Several therapies of this kind are under development for treatment of AML. Surprisingly, both in vitro and in vivo, a subset of these TCE immunocoached T cells (ICTs) can subsequently target autologous AML cells and mediate efficient TCR-MHC-dependent AML cell killing in the absence of the TCE. This points to that a) a portion of the T cells present in an AML are leukemia-reactive but have been immunosuppressed - a suppression that can be reversed by the addition of a TCE, b) that this anti-AML T cell reactivation may play an important part of the mechanism of action of AML-targeted TCEs and c) that by understanding this reactivation mechanism, we will be able to design improved AML immunotherapies in the future. Aims: To understand the mechanisms by which a TCE induces reactivation of leukemia-reactive T cells (LRTs) in AML. Methods: T cells in biobanked AML patient bone marrow samples were activated with either an anti-CD3 x anti-CD123 TCE or a conventional anti-CD3 antibody for 5 days before isolating the ICTs. ICT assay: ICTs were washed to remove the TCE, and isolated ICTs were co-cultured with additional autologous bone marrow cells at different E:T ratios. Killing efficiency and T cell expansion were determined over several days using flow cytometry. Trogocytosis assay: ICTs were co-cultured with stained additional autologous AML cells for 1 h and T cell populations of interest were isolated using FACS. T cell repertoires were analyzed by targeted RNAseq of the TCR. Results: ICTs generated with a TCE kill autologous AML cells efficiently without further addition of the TCE. Adding additional TCE at this stage also does not increase the AML killing efficiency of the ICTs. ICTs generated with an activating anti-CD3 antibody show a similar AML killing efficiency and a similar trogocytotic behavior as TCE ICTs. Most of the TCR clones present in the AML bone marrow pre-stimulation were also represented among the ICTs and trogocytotic ICTs (ICTs that are directly targeting the AML cells after either TCE or anti-CD3 stimulation; Figure 1), suggesting that the bulk of T cells in an AML bone marrow represent heterogeneous immunosuppressed LRTs which can be equally well reactivated by a TCE or an anti-CD3 antibody. Trogocytotic ICTs generated from both types of T cell activation have a similar TCR distribution. ICTs derived from the bone marrow target autologous AML cells more efficiently than ICTs from peripheral blood. Image:Summary/Conclusion: Similarities between TCE ICTs and CD3 ICTs in regards to TCR distributions and killing efficiencies suggest that the TCE reactivates leukemia-reactive T cells via a CD3-dependent mechanism rather than a more complex proximity mechanism. Our data further suggests that T cells in the AML bone marrow are highly heterogeneous and leukemia targeted to a very high degree. In summary, AML bone marrow ICTs are targeting and killing leukemic cells efficiently in a polyclonal fashion and our results highlight that boosting this mechanism can leverage the clinical impact of AML TCEs and be utilized in other novel AML immunotherapy approaches.

Production of food-grade microcarriers based on by-products from the food industry to facilitate the expansion of bovine skeletal muscle satellite cells for cultured meat production

A major challenge for successful cultured meat production is the requirement for large quantities of skeletal muscle satellite cells (MuSCs). Commercial microcarriers (MCs), such as Cytodex®1, enable extensive cell expansion by offering a large surface-to-volume ratio. However, the cell-dissociation step post cell expansion makes the cell expansion less efficient. A solution is using food-grade MCs made of sustainable raw materials that do not require a dissociation step and can be included in the final meat product. This study aimed to produce food-grade MCs from food industry by-products (i.e., turkey collagen and eggshell membrane) and testing their ability to expand bovine MuSCs in spinner flask systems for eight days. The MCs’ physical properties were characterized, followed by analyzing the cell adhesion, growth, and metabolic activity. All MCs had an interconnected porous structure. Hybrid MCs composed of eggshell membrane and collagen increased the mechanical hardness and stabilized the buoyancy compared to pure collagen MCs. The MuSCs successively attached and covered the entire surface of all MCs while expressing high cell proliferation, metabolic activity, and low cell cytotoxicity. Cytodex®1 MCs were included in the study. Relative gene expression of skeletal muscle markers showed reduced PAX7 and increased MYF5, which together with augmented proliferation marker MKI67 indicated activated and proliferating MuSCs on all MCs. Furthermore, the expression pattern of cell adhesion receptors (ITGb5 and SDC4) and focal adhesion marker VCL varied between the distinct MCs, indicating different specific cell receptor interactions with the various biomaterials. Altogether, our results demonstrate that these biomaterials are promising prospects to produce custom-fabricated food-grade MCs intended to expand MuSCs.

Leveraging Antibody, B Cell and Fc Receptor Interactions to Understand Heterogeneous Immune Responses in Tuberculosis

Despite over a century of research, Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), continues to kill 1.5 million people annually. Though less than 10% of infected individuals develop active disease, the specific host immune responses that lead to Mtb transmission and death, as well as those that are protective, are not yet fully defined. Recent immune correlative studies demonstrate that the spectrum of infection and disease is more heterogenous than has been classically defined. Moreover, emerging translational and animal model data attribute a diverse immune repertoire to TB outcomes. Thus, protective and detrimental immune responses to Mtb likely encompass a framework that is broader than T helper type 1 (Th1) immunity. Antibodies, Fc receptor interactions and B cells are underexplored host responses to Mtb. Poised at the interface of initial bacterial host interactions and in granulomatous lesions, antibodies and Fc receptors expressed on macrophages, neutrophils, dendritic cells, natural killer cells, T and B cells have the potential to influence local and systemic adaptive immune responses. Broadening the paradigm of protective immunity will offer new paths to improve diagnostics and vaccines to reduce the morbidity and mortality of TB.

Construction and Validation of an Immune-Related Risk Score Model for Survival Prediction in Glioblastoma.

BackgroundAs one of the most important brain tumors, glioblastoma (GBM) has a poor prognosis, especially in adults. Immune-related genes (IRGs) and immune cell infiltration are responsible for the pathogenesis of GBM. This study aimed to identify new tumor markers to predict the prognosis of patients with GBM.MethodsThe Cancer Genome Atlas (TCGA) database and ImmPort database were used for model construction. The Wilcoxon rank-sum test was applied to identify the differentially expressed IRGs (DEIRGs) between the GBM and normal samples. Univariate Cox regression analysis and Kaplan–Meier analysis was performed to investigate the relationship between each DEIRG and overall survival. Next, multivariate Cox regression analysis was exploited to further explore the prognostic potential of DEIRGs. A risk-score model was constructed based on the above results. The area under the curve (AUC) values were calculated to assess the effect of the model prediction. Furthermore, the Chinese Glioma Genome Atlas (CGGA) dataset was used for model validation. STRING database and functional enrichment analysis were used for exploring the gene interactions and the underlying functions and pathways. The CIBERSORT algorithm was used for correlation analysis of the marker genes and the tumor-infiltrating immune cells.ResultsThere were 198 DEIRGs in GBM, including 153 upregulated genes and 45 downregulated genes. Seven marker genes (LYNX1, PRELID1P4, MMP9, TCF12, RGS14, RUNX1, and CCR2) were filtered out by sequential screening for DEIRGs. The regression coefficients (0.0410, 1.335, 0.005, −0.021, 0.123, 0.142, and −0.329) and expression data of the marker genes were used to construct the model. The AUC values for 1, 2, and 3 years were 0.744, 0.737, and 0.749 in the TCGA–GBM cohort and 0.612, 0.602, and 0.594 in the CGGA-GBM cohort, respectively, which indicated a high predictive power. The results of enrichment analysis revealed that these genes were enriched in the activation of T cell and cytokine receptor interaction pathways. The interaction network map demonstrated a close relationship between the marker genes MMP9 and CCR2. Infiltration analysis of the immune cells showed that dendritic cells (DCs) could identify GBM, while LYNX1, RUNX1, and CCR2 were significantly positively correlated with DCs expression.ConclusionThis study analyzed the expression of IRGs in GBM and identified seven marker genes for the construction of an immune-related risk score model. These marker genes were found to be associated with DCs and were enriched in similar immune response pathways. These findings are likely to provide new insights for the immunotherapy of patients with GBM.

Fluctuations in T cell receptor and pMHC interactions regulate T cell activation.

Adaptive immune responses depend on interactions between T cell receptors (TCRs) and peptide major histocompatibility complex (pMHC) ligands located on the surface of T cells and antigen presenting cells (APCs), respectively. As TCRs and pMHCs are often only present at low copy numbers their interactions are inherently stochastic, yet the role of stochastic fluctuations on T cell function is unclear. Here, we introduce a minimal stochastic model of T cell activation that accounts for serial TCR-pMHC engagement, reversible TCR conformational change and TCR aggregation. Analysis of this model indicates that it is not the strength of binding between the T cell and the APC cell per se that elicits an immune response, but rather the information imparted to the T cell from the encounter, as assessed by the entropy rate of the TCR-pMHC binding dynamics. This view provides an information-theoretic interpretation of T cell activation that explains a range of experimental observations. Based on this analysis, we propose that effective T cell therapeutics may be enhanced by optimizing the inherent stochasticity of TCR-pMHC binding dynamics.