Monitoring Immune Responses to Vaccination: A Focus on Single-Cell Analysis and Associated Challenges

Abstract

Monitoring the immune response to vaccination encompasses both significant challenges and promising opportunities for scientific advancement. The primary challenge lies in the inherent complexity and interindividual variability of immune responses, influenced by factors including age, genetic background, and prior immunological history. This variability necessitates the development of sophisticated, highly sensitive assays capable of accurately quantifying immune parameters such as antibody titers, T-cell responses, and cytokine profiles. Furthermore, the temporal dynamics of the immune response require comprehensive longitudinal studies to elucidate the durability and quality of vaccine-induced immunity. Challenges of this magnitude pave the way for immunological research advancements and diagnostic methodologies. Cutting-edge monitoring techniques, such as high-throughput sequencing and advanced flow cytometry, enable deeper insights into the mechanistic underpinnings of vaccine efficacy and contribute to the iterative design of more effective vaccines. Additionally, the integration of analytical tools holds the potential to predict immune responses and tailor personalized vaccination strategies. This will be addressed in this review to provide insight for enhancing public health outcomes and fortifying preparedness against future infectious disease threats.

Keywords: flow cytometry; immune response; reproducibility; vaccination.

Figure 1

The temporality of the immune response following vaccination. Following vaccination, the antigen-presenting cells migrate to lymph nodes and initiate the immune response, including inflammation leading to activation of the corresponding T cells, which in turn help B cells to produce antibodies (IgM and then IgG). DC: dendritic cells; PRR: pattern recognition receptor; Ig: immunoglobin.

Figure 2

Technologies used to monitor responses to vaccination. Following blood sampling, analysis of whole blood or isolation of PBMC is performed. The plaque reduction neutralization test is used to quantify the titer of neutralizing antibodies for a virus. The serum is diluted and mixed with a viral suspension to allow the present antibodies to react with the virus. The effect of antibodies on the hemagglutination process, by which a virus binds to red blood cells, is measured with the hemagglutination inhibition assay rather than the titer needed to block the cytopathic effects of the virus. It is only a correlation of the ability of antibodies to inhibit virus infection of host cells. Analysis of soluble markers of the response (antibody levels, cytokines) can now be easily multiplexed with recent innovations. The cellular response is more often performed using high-dimension and single-cell analysis. Single-cell analysis can be performed with single-cell sorting before RNA sequencing (scRNA-seq). The analysis of immune cell composition from a dried blood spot has been shown to be possible by flow cytometry.

Figure 3

Advanced single-cell data analysis. (A) Automated identification of clusters of major cell populations based on fluorescence reported overlayed on a t-distributed stochastic neighbor embedding (t-SNE) map in a PBMC sample from a healthy donor. This enables the identification of populations as well as inter- and intra-comparisons. (B) Self-organizing map (SOM) resulting from a FlowSOM run on a PBMC sample from a healthy donor. The map identifies major clusters with colors indicating marker expression. (C) UMAP run with default settings on CD45+ cells in a PBMC sample from a healthy donor stained with a 40-color panel. Z channel for coloring CD45RA. Pseudotime representation enabling tracking of cell maturation/differentiation. (D) Results of a CITRUS run with a PAMR (nearest shrunken centroid model) used to identify clusters of cells with similar phenotypes that have a significantly different abundance between two groups of samples.

Figure 4

Reducing the variability in flow cytometry analysis. The standardization of cytometers enables comparisons of immunological data across various sites, as well as sites where different equipment is used for the same study. Automation can be integrated during various steps of experimental design, including sample preparation, cell stimulation, cell staining, and washing steps before analysis. The use of ready-to-use antibody mixes reduces the variability introduced by manual pipetting. Some ready-to-use mixes have a long shelf life (up to two years) with reduced logistical constraints. Another option is to introduce cell barcoding to the experimental design or to analyze samples from diverse study groups in the same batch. Ensuring the cytometer is well calibrated and controls are properly introduced will also reduce the variability and enable the normalization of data if required. Finally, automated analysis can be ideal for relieving the heavy burden as well as the subjectiveness of data analysis.