The T-cell-directed vaccine BNT162b4 encoding conserved non-spike antigens protects animals from severe SARS-CoV-2 infection.

T cell responses play an important role in protection against beta-coronavirus infections, including SARS-CoV-2, where they associate with decreased COVID-19 disease severity and duration. To enhance T cell immunity across epitopes infrequently altered in SARS-CoV-2 variants, we designed BNT162b4, an mRNA vaccine component that is intended to be combined with BNT162b2, the spike-protein-encoding vaccine. BNT162b4 encodes variant-conserved, immunogenic segments of the SARS-CoV-2 nucleocapsid, membrane, and ORF1ab proteins, targeting diverse HLA alleles. BNT162b4 elicits polyfunctional CD4+ and CD8+ T cell responses to diverse epitopes in animal models, alone or when co-administered with BNT162b2 while preserving spike-specific immunity. Importantly, we demonstrate that BNT162b4 protects hamsters from severe disease and reduces viral titers following challenge with viral variants. These data suggest that a combination of BNT162b2 and BNT162b4 could reduce COVID-19 disease severity and duration caused by circulating or future variants. BNT162b4 is currently being clinically evaluated in combination with the BA.4/BA.5 Omicron-updated bivalent BNT162b2 (NCT05541861).

A Phase Ib Trial of Personalized Neoantigen Therapy Plus Anti-PD-1 in Patients with Advanced Melanoma, Non-small Cell Lung Cancer, or Bladder Cancer.

Neoantigens arise from mutations in cancer cells and are important targets of T cell-mediated anti-tumor immunity. Here, we report the first open-label, phase Ib clinical trial of a personalized neoantigen-based vaccine, NEO-PV-01, in combination with PD-1 blockade in patients with advanced melanoma, non-small cell lung cancer, or bladder cancer. This analysis of 82 patients demonstrated that the regimen was safe, with no treatment-related serious adverse events observed. De novo neoantigen-specific CD4+ and CD8+ T cell responses were observed post-vaccination in all of the patients. The vaccine-induced T cells had a cytotoxic phenotype and were capable of trafficking to the tumor and mediating cell killing. In addition, epitope spread to neoantigens not included in the vaccine was detected post-vaccination. These data support the safety and immunogenicity of this regimen in patients with advanced solid tumors (Clinicaltrials.gov: NCT02897765).

Defining HLA-II Ligand Processing and Binding Rules with Mass Spectrometry Enhances Cancer Epitope Prediction.

Increasing evidence indicates CD4+ T cells can recognize cancer-specific antigens and control tumor growth. However, it remains difficult to predict the antigens that will be presented by human leukocyte antigen class II molecules (HLA-II), hindering efforts to optimally target them therapeutically. Obstacles include inaccurate peptide-binding prediction and unsolved complexities of the HLA-II pathway. To address these challenges, we developed an improved technology for discovering HLA-II binding motifs and conducted a comprehensive analysis of tumor ligandomes to learn processing rules relevant in the tumor microenvironment. We profiled >40 HLA-II alleles and showed that binding motifs were highly sensitive to HLA-DM, a peptide-loading chaperone. We also revealed that intratumoral HLA-II presentation was dominated by professional antigen-presenting cells (APCs) rather than cancer cells. Integrating these observations, we developed algorithms that accurately predicted APC ligandomes, including peptides from phagocytosed cancer cells. These tools and biological insights will enable improved HLA-II-directed cancer therapies.

APOBEC2 safeguards skeletal muscle cell fate through binding chromatin and regulating transcription of non-muscle genes during myoblast differentiation.

The apolipoprotein B messenger RNA editing enzyme, catalytic polypeptide (APOBEC) family is composed of nucleic acid editors with roles ranging from antibody diversification to RNA editing. APOBEC2, a member of this family with an evolutionarily conserved nucleic acid-binding cytidine deaminase domain, has neither an established substrate nor function. Using a cellular model of muscle differentiation where APOBEC2 is inducibly expressed, we confirmed that APOBEC2 does not have the attributed molecular functions of the APOBEC family, such as RNA editing, DNA demethylation, and DNA mutation. Instead, we found that during muscle differentiation APOBEC2 occupied a specific motif within promoter regions; its removal from those regions resulted in transcriptional changes. Mechanistically, these changes reflect the direct interaction of APOBEC2 with histone deacetylase (HDAC) transcriptional corepressor complexes. We also found that APOBEC2 could bind DNA directly, in a sequence-specific fashion, suggesting that it functions as a recruiter of HDAC to specific genes whose promoters it occupies. These genes are normally suppressed during muscle cell differentiation, and their suppression may contribute to the safeguarding of muscle cell fate. Altogether, our results reveal a unique role for APOBEC2 within the APOBEC family.

Epitranscriptomic profiling across cell types reveals associations between APOBEC1-mediated RNA editing, gene expression outcomes, and cellular function.

Epitranscriptomics refers to posttranscriptional alterations on an mRNA sequence that are dynamic and reproducible, and affect gene expression in a similar way to epigenetic modifications. However, the functional relevance of those modifications for the transcript, the cell, and the organism remain poorly understood. Here, we focus on RNA editing and show that Apolipoprotein B mRNA-editing enzyme, catalytic polypeptide-1 (APOBEC1), together with its cofactor RBM47, mediates robust editing in different tissues. The majority of editing events alter the sequence of the 3'UTR of targeted transcripts, and we focus on one cell type (monocytes) and on a small set of highly edited transcripts within it to show that editing alters gene expression by modulating translation (but not RNA stability or localization). We further show that specific cellular processes (phagocytosis and transendothelial migration) are enriched for transcripts that are targets of editing and that editing alters their function. Finally, we survey bone marrow progenitors and demonstrate that common monocyte progenitor cells express high levels of APOBEC1 and are susceptible to loss of the editing enzyme. Overall, APOBEC1-mediated transcriptome diversification is required for the fine-tuning of protein expression in monocytes, suggesting an epitranscriptomic mechanism for the proper maintenance of homeostasis in innate immune cells.

Loss of APOBEC1 RNA-editing function in microglia exacerbates age-related CNS pathophysiology.

Microglia (MG), a heterogeneous population of phagocytic cells, play important roles in central nervous system (CNS) homeostasis and neural plasticity. Under steady-state conditions, MG maintain homeostasis by producing antiinflammatory cytokines and neurotrophic factors, support myelin production, and remove synapses and cellular debris, as well as participating in "cross-correction," a process that supplies neurons with key factors for executing autophagy-lysosomal function. As sentinels for the immune system, MG also detect "danger" signals (pathogenic or traumatic insult), become activated, produce proinflammatory cytokines, and recruit monocytes and dendritic cells to the site of damage through a breached blood-brain barrier or via brain lymphatics. Failure to effectively resolve MG activation can be problematic and can lead to chronic inflammation, a condition proposed to underlie CNS pathophysiology in heritable brain disorders and age-related neurodegenerative and cognitive decline. Here, we show that APOBEC1-mediated RNA editing occurs within MG and is key to maintaining their resting status. Like bone marrow-derived macrophages, RNA editing in MG leads to overall changes in the abundance of edited proteins that coordinate the function of multiple cellular pathways. Conversely, mice lacking the APOBEC1 editing function in MG display evidence of dysregulation, with progressive age-related signs of neurodegeneration, characterized by clustering of activated MG, aberrant myelination, increased inflammation, and lysosomal anomalies that culminate in behavioral and motor deficiencies. Collectively, our study identifies posttranscriptional modification by RNA editing as a critical regulatory mechanism of vital cellular functions that maintain overall brain health.

Controlling and assessing the surface display of cell-binding domains on magnetite conjugated fluorescent liposomes.

Biological systems provide us with a diverse source of peptide-based ligands for cellular adhesion. Controlling and assessing the ligand surface density as well as tailoring the surface chemistry to have specific cellular adhesion properties are important in biomaterials design. In the following work, we provide a means for displaying peptide-based ligands on magnetic liposomes in which the surface density and chemistry may be controlled. Simultaneously, the conjugated vesicles provide a fluorescent signal for examining steric hindrance among surface ligands. In addition, the inherent magnetic and fluorescence features of this system revealed potential for magnet-based cell isolation and fluorescent labeling of adhered cells, respectively. Adhered cells were found to remain viable and proliferative, thereby allowing them to be used for subsequent evaluation. In a specific demonstration, we control the density of fibronectin-mimetic ligands on the polydiacetylene liposome surfaces. We find that steric limitation occurring at over 20% surface density result in decreased cell adhesion, in accord with related techniques. The magnetic-liposome system offers the means for not only separating cells adhered to the biomaterial, but also providing the ability to control and assess the biomaterial surface. This may prove particularly useful for examining combinations of peptide-based ligands or for evaluating the molecular-level ligand accessibility and its effect on cell attachment to a biomaterial surface.

A universal MHCII technology platform to characterize antigen-specific CD4+ T cells.

CD4+ T cells are critical to the immune system and perform multiple functions; therefore, their identification and characterization are crucial to better understanding the immune system in both health and disease states. However, current methods rarely preserve their ex vivo phenotype, thus limiting our understanding of their in vivo functions. Here we introduce a flexible, rapid, and robust platform for ex vivo CD4+ T cell identification. By combining MHCII allele purification, allele-independent peptide loading, and multiplexed flow cytometry technologies, we can enable high-throughput personalized CD4+ T cell identification, immunophenotyping, and sorting. Using this platform in combination with single-cell sorting and multimodal analyses, we identified and characterized antigen-specific CD4+ T cells relevant to COVID-19 and cancer neoantigen immunotherapy. Overall, our platform can be used to detect and characterize CD4+ T cells across multiple diseases, with potential to guide CD4+ T cell epitope design for any disease-specific immunization strategy.

Matrix mechanics and receptor-ligand interactions in cell adhesion.

Cell adhesions to both soluble and insoluble extracellular matrix ligands are critical in inter and intra-cellular signaling that mediates numerous physiological processes. These adhesions are complex structures composed of many scaffolding and signaling proteins. There are four distinct types of cell-matrix adhesions: focal complexes, focal adhesions, fibrillar adhesions, and 3D cell-matrix adhesions, which vary in composition, organization and function. The primary mediators of cell-matrix adhesions are integrins, which are mechanosensitive transmembrane receptor proteins that directly bind to matrix ligands to initiate adhesion formation. The development of cell-matrix adhesions is affected by a number of factors including matrix properties such as dimensionality and rigidity, and forces, both internally and externally generated, exerted on the adhesion sites. In this article, we discuss how matrix mechanics and forces affect the assembly and maturation of cell-matrix adhesions.

A Requirement for Argonaute 4 in Mammalian Antiviral Defense.

While interferon (IFN) responses are critical for mammalian antiviral defense, induction of antiviral RNA interference (RNAi) is evident. To date, individual functions of the mammalian RNAi and micro RNA (miRNA) effector proteins Argonautes 1-4 (AGO1-AGO4) during virus infection remain undetermined. AGO2 was recently implicated in mammalian antiviral defense, so we examined antiviral activity of AGO1, AGO3, or AGO4 in IFN-competent immune cells. Only AGO4-deficient cells are hyper-susceptible to virus infection. AGO4 antiviral function is both IFN dependent and IFN independent, since AGO4 promotes IFN but also maintains antiviral capacity following prevention of IFN signaling or production. We identified AGO-loaded virus-derived short interfering RNAs (vsiRNAs), a molecular marker of antiviral RNAi, in macrophages infected with influenza or influenza lacking the IFN and RNAi suppressor NS1, which are uniquely diminished without AGO4. Importantly, AGO4-deficient influenza-infected mice have significantly higher burden and viral titers in vivo. Together, our data assign an essential role for AGO4 in mammalian antiviral defense.

Sequence-based prediction of SARS-CoV-2 vaccine targets using a mass spectrometry-based bioinformatics predictor identifies immunogenic T cell epitopes.

BACKGROUND: The ongoing COVID-19 pandemic has created an urgency to identify novel vaccine targets for protective immunity against SARS-CoV-2. Early reports identify protective roles for both humoral and cell-mediated immunity for SARS-CoV-2. METHODS: We leveraged our bioinformatics binding prediction tools for human leukocyte antigen (HLA)-I and HLA-II alleles that were developed using mass spectrometry-based profiling of individual HLA-I and HLA-II alleles to predict peptide binding to diverse allele sets. We applied these binding predictors to viral genomes from the Coronaviridae family and specifically focused on T cell epitopes from SARS-CoV-2 proteins. We assayed a subset of these epitopes in a T cell induction assay for their ability to elicit CD8+ T cell responses. RESULTS: We first validated HLA-I and HLA-II predictions on Coronaviridae family epitopes deposited in the Virus Pathogen Database and Analysis Resource (ViPR) database. We then utilized our HLA-I and HLA-II predictors to identify 11,897 HLA-I and 8046 HLA-II candidate peptides which were highly ranked for binding across 13 open reading frames (ORFs) of SARS-CoV-2. These peptides are predicted to provide over 99% allele coverage for the US, European, and Asian populations. From our SARS-CoV-2-predicted peptide-HLA-I allele pairs, 374 pairs identically matched what was previously reported in the ViPR database, originating from other coronaviruses with identical sequences. Of these pairs, 333 (89%) had a positive HLA binding assay result, reinforcing the validity of our predictions. We then demonstrated that a subset of these highly predicted epitopes were immunogenic based on their recognition by specific CD8+ T cells in healthy human donor peripheral blood mononuclear cells (PBMCs). Finally, we characterized the expression of SARS-CoV-2 proteins in virally infected cells to prioritize those which could be potential targets for T cell immunity. CONCLUSIONS: Using our bioinformatics platform, we identify multiple putative epitopes that are potential targets for CD4+ and CD8+ T cells, whose HLA binding properties cover nearly the entire population. We also confirm that our binding predictors can predict epitopes eliciting CD8+ T cell responses from multiple SARS-CoV-2 proteins. Protein expression and population HLA allele coverage, combined with the ability to identify T cell epitopes, should be considered in SARS-CoV-2 vaccine design strategies and immune monitoring.

RNA editing generates cellular subsets with diverse sequence within populations.

RNA editing is a mutational mechanism that specifically alters the nucleotide content in transcribed RNA. However, editing rates vary widely, and could result from equivalent editing amongst individual cells, or represent an average of variable editing within a population. Here we present a hierarchical Bayesian model that quantifies the variance of editing rates at specific sites using RNA-seq data from both single cells, and a cognate bulk sample to distinguish between these two possibilities. The model predicts high variance for specific edited sites in murine macrophages and dendritic cells, findings that we validated experimentally by using targeted amplification of specific editable transcripts from single cells. The model also predicts changes in variance in editing rates for specific sites in dendritic cells during the course of LPS stimulation. Our data demonstrate substantial variance in editing signatures amongst single cells, supporting the notion that RNA editing generates diversity within cellular populations.

RNA Editing Dynamically Rewrites the Cancer Code.

Global analyses of cancer transcriptomes demonstrate that ADAR (adenosine deaminase, RNA-specific)-mediated RNA editing dynamically contributes to genetic alterations in cancer, and directly correlates with progression and prognosis. RNA editing is abundant and frequently elevated in cancer, and affects functionally and clinically relevant sites in both coding and non-coding regions of the transcriptome. Therefore, ADAR and differentially edited transcripts may be promising biomarkers or targets for therapy.

Modeling extracellular matrix reorganization in 3D environments.

Extracellular matrix (ECM) remodeling is a key physiological process that occurs in a number of contexts, including cell migration, and is especially important for cellular form and function in three-dimensional (3D) matrices. However, there have been few attempts to computationally model how cells modify their environment in a manner that accounts for both cellular properties and the architecture of the surrounding ECM. To this end, we have developed and validated a novel model to simulate matrix remodeling that explicitly defines cells in a 3D collagenous matrix. In our simulation, cells can degrade, deposit, or pull on local fibers, depending on the fiber density around each cell. The cells can also move within the 3D matrix. Different cell phenotypes can be modeled by varying key cellular parameters. Using the model we have studied how two model cancer cell lines, of differing invasiveness, modify matrices with varying fiber density in their vicinity by tracking the metric of fraction of matrix occupied by fibers. Our results quantitatively demonstrate that in low density environments, cells deposit more collagen to uniformly increase fibril fraction. On the other hand, in higher density environments, the less invasive model cell line reduced the fibril fraction as compared to the highly invasive phenotype. These results show good qualitative and quantitative agreement with existing experimental literature. Our simulation is therefore able to function as a novel platform to provide new insights into the clinically relevant and physiologically critical process of matrix remodeling by helping identify critical parameters that dictate cellular behavior in complex native-like environments.

Quantitative analysis of the effect of cancer invasiveness and collagen concentration on 3D matrix remodeling.

Extracellular matrix (ECM) remodeling is a key component of cell migration and tumor metastasis, and has been associated with cancer progression. Despite the importance of matrix remodeling, systematic and quantitative studies on the process have largely been lacking. Furthermore, it remains unclear if the disrupted tensional homeostasis characteristic of malignancy is due to initially altered ECM and tissue properties, or to the alteration of the tissue by tumor cells. To explore these questions, we studied matrix remodeling by two different prostate cancer cell lines in a three-dimensional collagen system. Over one week, we monitored structural changes in gels of varying collagen content using confocal reflection microscopy and quantitative image analysis, tracking metrics of fibril fraction, pore size, and fiber length and diameter. Gels that were seeded with no cells (control), LNCaP cells, and DU-145 cells were quantitatively compared. Gels with higher collagen content initially had smaller pore sizes and higher fibril fractions, as expected. However, over time, LNCaP- and DU-145-populated matrices showed different structural properties compared both to each other and to the control gels, with LNCaP cells appearing to favor microenvironments with lower collagen fiber fractions and larger pores than DU-145 cells. We posit that the DU-145 cells' preference for denser matrices is due to their higher invasiveness and proteolytic capabilities. Inhibition of matrix proteases resulted in reduced fibril fractions for high concentration gels seeded with either cell type, supporting our hypothesis. Our novel quantitative results probe the dynamics of gel remodeling in three dimensions and suggest that prostate cancer cells remodel their ECM in a synergistic manner that is dependent on both initial matrix properties as well as their invasiveness.

Computational study of proteolysis-driven single cell migration in a three-dimensional matrix.

Cell migration is a fundamental process that is crucial to a variety of physiological events. While traditional approaches have focused on two-dimensional (2D) systems, recent efforts have shifted to studying migration in three-dimensional (3D) matrices. A major distinction that has emerged is the increased importance of cell-matrix interactions in 3D environments. In particular, cell motility in 3D matrices is more dependent on matrix metalloproteinases (MMPs) to degrade steric obstacles than in 2D systems. In this study, we implement the effects of MMP-mediated proteolysis in a force-based computational model of 3D migration, testing two matrix ligand-MMP relationships that have been observed experimentally: linear and log-linear. The model for both scenarios predicts maximal motility at intermediate matrix ligand and MMP levels, with the linear case providing more physiologically compelling results. Recent experimental results suggesting MMP influence on integrin expression are also integrated into the model. While the biphasic behavior is retained, with MMP-integrin feedback peak cell speed is observed in a low ligand, high MMP regime instead of at intermediate ligand and MMP levels for both ligand-MMP relationships. The simulation provides insight into the expanding role of cell-matrix interactions in cell migration in 3D environments and has implications for cancer research.