Single-Cell Analysis of Antigen-Specific CD8+ T-Cell Transcripts Reveals Profiles Specific to mRNA or Adjuvanted Protein Vaccines

Transcriptional Systems Vaccinology Approaches for Vaccine Adjuvant Profiling

Adjuvants are a diverse group of substances that can be added to vaccines to enhance antigen-specific immune responses and improve vaccine efficacy. The first adjuvants, discovered almost a century ago, were soluble crystals of aluminium salts. Over the following decades, oil emulsions, vesicles, oligodeoxynucleotides, viral capsids, and other complex organic structures have been shown to have adjuvant potential. However, the detailed mechanisms of how adjuvants enhance immune responses remain poorly understood and may be a barrier that reduces the rational selection of vaccine components. Previous studies on mechanisms of action of adjuvants have focused on how they activate innate immune responses, including the regulation of cell recruitment and activation, cytokine/chemokine production, and the regulation of some "immune" genes. This approach provides a narrow perspective on the complex events involved in how adjuvants modulate antigen-specific immune responses. A comprehensive and efficient way to investigate the molecular mechanism of action for adjuvants is to utilize systems biology approaches such as transcriptomics in so-called "systems vaccinology" analysis. While other molecular biology methods can verify if one or few genes are differentially regulated in response to vaccination, systems vaccinology provides a more comprehensive picture by simultaneously identifying the hundreds or thousands of genes that interact with complex networks in response to a vaccine. Transcriptomics tools such as RNA sequencing (RNA-Seq) allow us to simultaneously quantify the expression of practically all expressed genes, making it possible to make inferences that are only possible when considering the system as a whole. Here, we review some of the challenges in adjuvant studies, such as predicting adjuvant activity and toxicity when administered alone or in combination with antigens, or classifying adjuvants in groups with similar properties, while underscoring the significance of transcriptomics in systems vaccinology approaches to propel vaccine development forward.

Optimizing immunogenicity and product presentation of a SARS-CoV-2 subunit vaccine composition: effects of delivery route, heterologous regimens with self-amplifying RNA vaccines, and lyophilization

Introduction

Dozens of vaccines have been approved or authorized internationally in response to the ongoing SARS-CoV-2 pandemic, covering a range of modalities and routes of delivery. For example, mucosal delivery of vaccines via the intranasal (i.n.) route has been shown to improve protective mucosal responses in comparison to intramuscular (i.m.) delivery. As we gain knowledge of the limitations of existing vaccines, it is of interest to understand if changes in product presentation or combinations of multiple vaccine modalities can further improve immunological outcomes.

Methods

We investigated a commercial-stage SARS-CoV-2 receptor binding domain (RBD) antigen adjuvanted with a clinical-stage TLR-7/8 agonist (3M-052) formulated on aluminum oxyhydroxide (Alum). In a murine immunogenicity model, we compared i.n. and i.m. dosing of the RBD-3M-052-Alum vaccine. We measured the magnitude of antibody responses in serum and lungs, the antibody-secreting cell populations in bone marrow, and antigen-specific cytokine-secreting splenocyte populations. Similarly, we compared different heterologous and homologous prime-boost regimens using the RBD-3M-052-Alum vaccine and a clinical-stage self-amplifying RNA (saRNA) vaccine formulated on a nanostructured lipid carrier (NLC) using the i.m. route alone. Finally, we developed a lyophilized presentation of the RBD-3M-052-Alum vaccine and compared it to the liquid presentation and a heterologous regimen including a previously characterized lyophilized form of the saRNA-NLC vaccine.

Results and discussion

We demonstrate that i.n. dosing of the RBD-3M-052-Alum vaccine increased IgA titers in the lung by more than 1.5 logs, but induced serum IgG titers 0.8 logs lower, in comparison to i.m. dosing of the same vaccine. We also show that the homologous prime-boost RBD-3M-052-Alum regimen led to the highest serum IgG and bronchial IgA titers, whereas the homologous saRNA-NLC regimen led to the highest splenocyte interferon-γ response. We found that priming with the saRNA-NLC vaccine and boosting with the RBD-3M-052-Alum vaccine led to the most desirable immune outcome of all regimens tested. Finally, we show that the lyophilized RBD-3M-052-Alum vaccine retained its immunological characteristics. Our results demonstrate that the route of delivery and the use of heterologous regimens each separately impacts the resulting immune profile, and confirm that multi-product vaccine regimens can be developed with stabilized presentations in mind.

SifiNet: a robust and accurate method to identify feature gene sets and annotate cells

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multi-omic cellular profiles. It is conveniently available as an open-source R package.

SifiNet: A robust and accurate method to identify feature gene sets and annotate cells

SifiNet is a robust and accurate computational pipeline for identifying distinct gene sets, extracting and annotating cellular subpopulations, and elucidating intrinsic relationships among these subpopulations. Uniquely, SifiNet bypasses the cell clustering stage, commonly integrated into other cellular annotation pipelines, thereby circumventing potential inaccuracies in clustering that may compromise subsequent analyses. Consequently, SifiNet has demonstrated superior performance in multiple experimental datasets compared with other state-of-the-art methods. SifiNet can analyze both single-cell RNA and ATAC sequencing data, thereby rendering comprehensive multiomic cellular profiles. It is conveniently available as an open-source R package.

MRI/PET multimodal imaging of the innate immune response in skeletal muscle and draining lymph node post vaccination in rats

The goal of this study was to utilize a multimodal magnetic resonance imaging (MRI) and positron emission tomography (PET) imaging approach to assess the local innate immune response in skeletal muscle and draining lymph node following vaccination in rats using two different vaccine platforms (AS01 adjuvanted protein and lipid nanoparticle (LNP) encapsulated Self-Amplifying mRNA (SAM)). MRI and ¹⁸FDG PET imaging were performed temporally at baseline, 4, 24, 48, and 72 hr post Prime and Prime-Boost vaccination in hindlimb with Cytomegalovirus (CMV) gB and pentamer proteins formulated with AS01, LNP encapsulated CMV gB protein-encoding SAM (CMV SAM), AS01 or with LNP carrier controls. Both CMV AS01 and CMV SAM resulted in a rapid MRI and PET signal enhancement in hindlimb muscles and draining popliteal lymph node reflecting innate and possibly adaptive immune response. MRI signal enhancement and total ¹⁸FDG uptake observed in the hindlimb was greater in the CMV SAM vs CMV AS01 group (↑2.3 - 4.3-fold in AUC) and the MRI signal enhancement peak and duration were temporally shifted right in the CMV SAM group following both Prime and Prime-Boost administration. While cytokine profiles were similar among groups, there was good temporal correlation only between IL-6, IL-13, and MRI/PET endpoints. Imaging mass cytometry was performed on lymph node sections at 72 hr post Prime and Prime-Boost vaccination to characterize the innate and adaptive immune cell signatures. Cell proximity analysis indicated that each follicular dendritic cell interacted with more follicular B cells in the CMV AS01 than in the CMV SAM group, supporting the stronger humoral immune response observed in the CMV AS01 group. A strong correlation between lymph node MRI T2 value and nearest-neighbor analysis of follicular dendritic cell and follicular B cells was observed (r=0.808, P<0.01). These data suggest that spatiotemporal imaging data together with AI/ML approaches may help establish whether in vivo imaging biomarkers can predict local and systemic immune responses following vaccination.

Tetramer-aided sorting and single-cell RNA sequencing facilitate transcriptional profiling of antigen-specific CD8+ T cells

BACKGROUND

Recent advances in single-cell technologies and an improved understanding of tumor antigens have empowered researchers to investigate tumor antigen-specific CD8+ T cells at the single-cell level. Peptide-MHC I tetramers are often utilized to enrich antigen-specific CD8+ T cells, which however, introduces the undesired risk of altering their clonal distribution or their transcriptional state. This study addresses the feasibility of utilizing tetramers to enrich antigen-specific CD8+ T cells for single-cell analysis.

METHODS

HLA-A*02:01-restricted human cytomegalovirus (CMV) pp65 peptide-specific CD8+ T cells were used as a model for analyzing antigen-specific CD8+ T cells. Single-cell RNA sequencing and TCR sequencing were performed to compare the frequency and gene expression profile of pp65-specific TCR clones between tetramer-sorted, unstimulated- and tetramer-stimulated total CD8+ T cells.

RESULTS

The relative frequency of pp65-specific TCR clones and their transcriptional profile remained largely unchanged following tetramer-based sorting. In contrast, tetramer-mediated stimulation of CD8+ T cells resulted in significant gene expression changes in pp65-specific CD8+ T cells. An Antigen-Specific Response (ASR) gene signature was derived from tetramer-stimulated pp65-specific CD8+ T cells. The ASR signature had a predictive value and was significantly associated with progression free survival in lung cancer patients treated with anti-PD-L1, anti-VEGF, chemotherapy combination (NCT02366143). The predictive power of the ASR signature was independent of the conventional CD8 effector signature.

CONCLUSIONS

Our findings validate the approach of enriching antigen-specific CD8+ T cells through tetramer-aided Fluorescence-Activated Cell Sorting (FACS) sorting for single-cell analysis and also identifies an ASR gene signature that has value in predicting response to cancer immunotherapy.