Computational Analysis of Multiparametric Flow Cytometric Data to Dissect B Cell Subsets in Vaccine Studies

Abstract

The generation of the B cell response upon vaccination is characterized by the induction of different functional and phenotypic subpopulations and is strongly dependent on the vaccine formulation, including the adjuvant used. Here, we have profiled the different B cell subsets elicited upon vaccination, using machine learning methods for interpreting high‐dimensional flow cytometry data sets. The B cell response elicited by an adjuvanted vaccine formulation, compared to the antigen alone, was characterized using two automated methods based on clustering (FlowSOM) and dimensional reduction (t‐SNE) approaches. The clustering method identified, based on multiple marker expression, different B cell populations, including plasmablasts, plasma cells, germinal center B cells and their subsets, while this profiling was more difficult with t‐SNE analysis. When undefined phenotypes were detected, their characterization could be improved by integrating the t‐SNE spatial visualization of cells with the FlowSOM clusters. The frequency of some cellular subsets, in particular plasma cells, was significantly higher in lymph nodes of mice primed with the adjuvanted formulation compared to antigen alone. Thanks to this automatic data analysis it was possible to identify, in an unbiased way, different B cell populations and also intermediate stages of cell differentiation elicited by immunization, thus providing a signature of B cell recall response that can be hardly obtained with the classical bidimensional gating analysis. © 2019 The Authors. Cytometry Part A published by Wiley Periodicals, Inc. on behalf of International Society for Advancement of Cytometry.

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“…When compared to the immune response elicited by the H56 antigen alone, this analysis also confirms the key role of the adjuvant in strongly reprogramming the immune response [ 10 ] and potentiating the vaccine immunogenicity as we also previously observed with other vaccine adjuvants [ 3 , 44 ], while no significant differences were observed in the antigen-specific IgG titers at the time points analyzed after the booster immunization.…”

Shelter from the cytokine storm: pitfalls and prospects in the development of SARS-CoV-2 vaccines for an elderly population

“…Currently, computational models have been applied to immunology data, for example, for the analysis of a high-dimensional dataset in vaccination studies [107,108], but these models are limited to particular aspects [109,110]. There is the potential for these models to become more sophisticated and to predict how responses to pathogens and vaccines are affected by pre-disposing factors [111,112].…”

From Bivariate to Multivariate Analysis of Cytometric Data: Overview of Computational Methods and Their Application in Vaccination Studies

“…Histograms and dot plots are used to display marker distribution in a cluster comparing with a parental population. Other approaches aim to visualize inter-cluster relationship, showing clusters centroids, cluster median values or frequency of positive cells with minimum spanning three (MST), heatmaps, scaffold map, and dimensionality reduction techniques [27,[54][55][56][57].…”

“…These subsets can be cells at intermediate stages of differentiation, or novel unexpected phenotypes. By applying the FlowSOM clustering approach different clusters of B cells elicited by immunization with a tuberculosis vaccine antigen combined with the liposome-based adjuvant CAF01 have been characterized [57]. Employing a computational approach, it was possible to identify many plasmablast subsets and different germinal center B cell subtypes.…”

“…Employing a computational approach, it was possible to identify many plasmablast subsets and different germinal center B cell subtypes. The clustering approach, followed by a statistical analysis between groups immunized with or without the adjuvant component, has allowed us to identify a group of plasma cells as a specific biomarker of immunization with the adjuvanted-vaccine formulation [57]. Another clustering tool, FLOCK, was used for characterizing seventeen different B-cell subsets in human blood and to identify and quantify novel plasmablast subsets responding transiently to tetanus and other vaccinations (diphtheria toxoid, trivalent influenza vaccine 2009, H1N1 monovalent influenza vaccine, Hepatitis A, and Hepatitis B) [32].…”