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Defining Cellular Subset Diversity in T-Cell Memory Responses to Vaccine Protocols

Posted on: December 09, 2020

The immune system not only has the power to respond to a foreign antigen, but it also has the amazing ability to remember it and then act quickly to a re-exposure. How the immune system accomplishes all of this is under research, but the impact of this knowledge offers great promise in the development of safer and more effective vaccines.  

A goal of any vaccine should include the stimulation of a robust effector T-cell response, which over time is translated into a large population of memory T-cells. Although the underlying mechanisms driving this process are not fully understood, and there are several models that have been proposed based on scientific findings across a variety of studies (Fig.1). These models describe various mechanisms for the differentiation of naïve T-cells into memory, either sequentially, or via specific cell subsets. The most recent research provides evidence that memory T-cells are generated from effector T-cells via epigenetic modifications, as the methylation patterns that are seen in memory cells are similar to those seen in effector cells. Whatever cellular mechanisms are involved in establishing memory T-cells, the ability to modulate immunological memory offers great promise across many fields of modern medicine.  

Defining CD8+ T-Cell Memory

CD8+ T-cell mediated immune responses are important in protection against various pathogens and specific tumor antigens associated with various cancers. This CD8+ T-cell population is made up of three subsets, naïve, effector, and memory T-cells. After antigen stimulation, these cells migrate into tissue areas that are inflamed where they exhibit a strong proliferative response and express and release cytokines that help to eliminate infection. The cells that mediate this response are known as effector memory T-cells (TEM ). Once the pathogen is cleared, most of these effector cells will undergo apoptosis to maintain the balance of the immune response. However, a small pool of long-lived memory cells is retained, and are primed to respond rapidly upon re-exposure to the pathogen. These are referred to as CD8+ memory T-cells because they ‘remember’ this previous encounter with the specific antigen, and they are programmed to elicit a faster and stronger immune response to that same antigen. This T-cell memory is the foundation of vaccine efficacy to establish immunological memory, resulting in tangible advances in population health. 

Defining CD4+ T-Cell Memory

Unlike the distinctive immunogenic pathway for CD8+ T-cell memory, CD4+ T-cell memory is significantly more plastic, involving at least seven distinct cell lineages with diverse effector functions, that play roles in all aspects of adaptive immunity as well as impact many innate immune mechanisms. The recruitment of the CD4+ subsets during the activation phase is influenced by the type of immunological threat, and they form a coordinated initiative during the expansion phase, to help balance the contribution of each branch of the adaptive immune response to effectively launch an effective,  threat-specific response.  Eradication of the threat during the contraction phase results in the loss through apoptosis of the majority of the adaptive immune effector cells. However, as with CD8+ T-cells, a small population of the responding cells survive and differentiate into long-lived memory cells. These cells are central to the development of adaptive immunity during the memory phase. CD4+ Th1 and Th2 memory T-cells are well described, in contrast, Th17, Tfh, Th9, Th22, and Treg lineages have proved more challenging to characterize due to a lack of consistent lineage fidelity.  

Fig. 1. Proposed mechanisms for the development of T-cell memory. A. The linear model describes the activation of naïve T-cells by the presentation of antigen-peptide on major histocompatibility complex (MHC) molecules by the antigen presenting cells (APCs) during the contraction phase of a T-cell response. This results in the generation of effector T-cells or memory precursors (yellow). The memory precursors give rise to effector memory T-cells (TEM) (red), central memory T-cells (TCM) (blue), and potentially to tissue-resident memory T-cells (TRM) (green). B. The asymmetrical or bifurcation model involves the development of TEM cells from proximal daughter cells (naïve T-cell- TCR + peptide and MHC-APC), while distal daughter cells give rise to TCM cells. C. In the self-renewal model, self-renewing effector T cells are generated from naïve T-cells and these can give rise to TEM cells. D. In the simultaneous model, the naïve T-cells differentiate into the different subsets, which further differentiate. Th1 and Th17 (dark grey) differentiate into effector T-cells, whereas follicular helper T cells (TFH) (light grey) generate the TCM cells. As with model C., the generation of tissue-resident memory-cells (TRM) has not been determined in this model (adapted from Raphael et. al. 2020).

Measuring T-cell Memory

Memory T-cells are designated into functional subsets based on phenotypic, cell surface markers that mediate the distinctive roles that T-cells play in orchestrating a targeted immune response. As such, flow cytometry provides a valuable tool for monitoring T-cell memory subsets. Naïve T cells express CD45A and homing the markers CD62L and CCR7. A typical naïve T-cell will express the following markers: CD45RA+, CD45RO-, CCR7+, CD62L+, CD27+, CD28+, IL-7Rα+. The homing markers allow the naïve T cells to travel from high endothelial venules (HEVs) to peripheral lymph nodes where they will interact with antigens that are presented to them by dendritic cells. The experience of exposure to their target antigen alters the phenotype of the T-cells by reducing the expression of CD45RA+ to a CD45RA- phenotype and activating the expression of CD45RO. These antigen experienced T cells are now known as T effector cells and upon engagement of their TC R with the target antigen, they release cytotoxic granules and specific effector cytokines whose actions help eliminate the pathogen. Traditionally these cells have been referred to as cytolytic CD4+ T cells. T effector cells are identified by the phenotype CD27low, CD28-, CD62L-, CCR7- but will express CD57 (NK marker) and KLGR-1 (Killer-cell lectin-like receptor subfamily G, member 1), that are markers for terminal activation.

Distinction of memory T-cell Subsets  

  1. Memory stem T-cells (TSCM) that reside in local lymphoid tissues and can respond immediately upon infection, they also express levels of CD95, IL-2Rβ, CXCR3 and LFA-1. 
  2. Central memory T-cells (TCM) that circulate in the blood and will target secondary lymphoid tissues. Central memory cells generally are identified by the phenotype: CD4+5RO+, CCR7+, CD27+, CD28+, CD62L high and do not possess lytic activity.
  3. Effector Memory T-cells (TEM) cells. CCR7 expression is often used to distinguish central memory cells from effector memory cells. Effector memory T-cells display the phenotype CD62low, CCR7- and display lytic activity. 

The phenotypes of memory T-cells are summarized below in Table 1 (Chatenoud, et.al. 1990). Recently a new subset of memory T-cells referred to as tissue-resident memory T-cells (TTR) have been identified. They are immune cells that live in peripheral tissues, are non-circulating, and are CD69+, CD103+. It appears that they mediate tumor protection via a combination of cytokine secretion and CD103-enhanced tumor cell killing.

 

Naïve

TSCM

TCM

TEM

T Effector

CD45RA

+++

++

++

+

CD45RO

+

+

+

CD44

+/−

+++

+/−

CCR7

+++

 

+++

+/−

CD62L

+++

+++

+++

+/−

CD127

+/+++

+++

+++

+

+/−

CD122

+

+++

+++

+

+/−

CD28

++

+++

+++

+

CD27

+/−

 

++

++

+/−

CD43

+/−

+++

CD95

+/−

 

+/−

++

+++

KLRG1

++

+++

Perforin

++

+++

Granzyme B

+

+++

Table 1. Phenotypes of Memory T-Cell Subsets.  While much is known regarding the effector and memory functions of CD4+ T-cells, the function of memory CD4+ T-cells is less well understood. CD4+ T-cells play an important role in immunity and carry out many functions such as activation, modulation, and regulation of both the adaptive and innate immune responses. The functions of CD4+ memory cells are important in mounting effective immune responses against various pathogens while balancing and maintaining self-tolerance to avoid undesired side-effects like attacks against self-tissues, organs, and cells. This delicate balance is accomplished by the secretion of certain cytokines, which act in concert with certain master regulatory transcription factors.

T cell Memory Homeostasis and Maintenance Following Vaccination.

Memory CD4+ T-cells are maintained for a lifetime through a long-term dynamic, homeostatic process that controls turnover based on perceived signals and responses.  This includes a stringent requirement for TcR signaling and MHC class II engagement, that may result in the selective survival of specific clones based on their propensity to receive signals from TcR; this could form the basis of the finding of expanded clones in aged individuals, presumably through the narrowing of the TcR repertoire of memory CD4+ T-cells over time (Lees and Farber, 2010). Throughout this, the memory CD4+ T-cell population remains highly plastic, and the inflammatory and cytokine environment can influence the outcome of memory T-cell responses, indicating that environmental cues can adjust the function of these cells and ultimately determine the efficacy of the response. 

Memory CD8+  T=cells are quite different though,  and although memory CD8+ T-cells decay overtime, their short term maintenance persists independent of TcR signaling and the engagement of MHC class I, and appears to rely on IL-15 and IL-7 for their survival. The down regulation of the lymphoid homing proteins CD62L and CCR7 in TEM limits these cells’ ability to reside in the lymph nodes, whereas TCM subsets are restricted to the lymphoid tissues through the high expression of these markers. These TCM subsets appear to represent a self-renewing pool of memory cells. In addition, a subset of memory T cells with naïve-like phenotypes, known as TSCM, that display homeostatic proliferate in response to IL-7 and IL-15, giving rise to multiple memory subsets and effector responses.   

The generation and maintenance of T-cell memory appears to be a very fluid process, with subsets of memory cells displaying different trafficking and metabolism profiles, along with variations in longevity, and transcriptional and epigenetic regulation that do not fit the classical definition of memory T-cells. These characteristics represent an overlapping continuum that may influence both the timing and potency of the immune recall response. This heterogeneity could potentially impact the efficacy of vaccines and protective immunity following an infection (Jameson et. al. 2018). The use of high-dimensional flow cytometry has enabled us to identify these various memory subsets and help us to stratify their unique and dynamic functions.  

The Importance of T-Cell Memory in Vaccine Development 

Several infectious diseases such as HIV and Ebola have no licensed vaccines available to prevent their spread; others such as malaria, tuberculosis (TB), and influenza have vaccines, but these vaccines are far from optimal and could be improved. An optimal vaccination processes induce two features:

  1. A robust antibody response that invokes a powerful effector immune response that results in the neutralization of the microbe and activation of the antimicrobial innate response. 
  2. Antigen-specific T-cell responses that support the antibody response, have direct effector functions, and activate innate effector cells such as macrophages and neutrophils. These T-cell responses should involve helper T-cells and/or cytotoxic T lymphocytes with memory and homing capacity, that are able to avoid exhaustion via negative feedback or immune checkpoint pathways. The ultimate goal is to establish long-lived CD8+ and CD4+ central memory cells that circulate through the secondary lymphoid organs and reside in the bone marrow in order to provide a concerted defense mechanism for effective pathogen clearance upon reinfection.

Characterization of T-cell subsets can be informative in understanding the mechanisms of vaccine efficacy. The establishment of T-cell memory follows the initial exposure of naïve T-cells to antigenic peptides complexed to MHC molecules on antigen presenting dendritic cells. These dendritic cells respond to the antigen via toll-like receptor ligands that activate the cells to express cytokines such as IL-12; these in turn influence the phenotypes of the responding T-cells e.g. Th1 cell biased is created when recognizing the presentation of antigen within the secondary lymphoid tissues. 

The profile of vaccination associated-T-cells in circulating PBMCs tends to follow a pattern of adaptive immune response, displaying a lag phase, followed by a peak at about 2 weeks, that then settles back down. Since memory is generated through this process, a second exposure generates an enhanced response, that causes the T-cells to reach a putative protective level. 

Ex vivo methods involving the exposure of whole blood or PBMCs to vaccine antigens have been used to evaluate vaccine efficacy, by examining bulk cytokine production using flow cytometry.  The most frequently measured cytokines produced in both CD4+ and CD8+ T-cells are IFN-γ, IL-2 and TNF-α. This profile can be expanded to examine the polyfunctionality of T-cells following in vitro antigen activation De. Rosea, 2012). However, flow cytometry can support numerous endpoints that are important in vaccine development (Table 2), such as the measurement of potential of cytotoxic T-cells by examining degranulation through the measurement of surface CD107a, and intracellular staining of Granzymes and Perforin. 


Assay


Profile Measured


Specific Markers


Activity Evaluated

Require Ex vivo antigen stimulation


ICS


Cytokines


IFN-γ, IL-2, TNF-α



Immunogenicity,

Polyfunctionality


Cytotoxic Potential

CD107a, granzymes, perforin


B-cell help


CD4+0L (CD154)


Memory Profile


CD4+5RA, CCR7, CD27, CD28


Memory Profile of antigen specific T-cells


CFSE proliferation


Proliferation


CFSE


Immunogenicity

Ex vivo Assays




Phenotyping


Activation Markers


HLA-DR, CD38, Ki-67, BcL-2


Kinetics of the immune response


Innate Markers


NK markers,

DC markers,

Monocyte markers


Early timepoint markers for innate response


Plasmablasts (transient 1-2 weeks post vaccination)


CD3, CD19, CD20, CD27, CD38


Frequency of plasmablasts

Cell Sorting for further characterization


Cell Sorting for down-stream analysis


Antigen-specific T-cell Isolation


CD137, CD4+0L, MHC class I or class II tetramers


Gene Expression profiles


Antigen-specific B-cell isolation


Plasmablast, antigen labeling


Antibody cloning

Table 2. Critical flow cytometry applications in vaccine development. The ability of flow cytometry to provide phenotypic and functional profiling of various cell types, enables this platform to play a central role in our understanding of the development of immunological responses to vaccination.

Perspectives for Vaccine Design.

Understanding the mechanisms of T-cell memory establishment and maintenance provide us with an opportunity to explore more rational vaccine design. Vaccines that imprint T-cells with the ability to deliver persistent activity against viral pathogens are under greater demand now than ever before. Identifying the initial programming signals is a key point in understanding the roles of priming and boosting in the establishment of effective memory T-cells, in both lymphoid and nonlymphoid tissues, and the overall effect these have for the development of more effective vaccination regimes.

In the case of Covid-19, there have been multiple pathways of vaccine development, from novel and cutting-edge DNA/RNA-based vaccines through to recombinant proteins and attenuated SARS-CoV-2 virus. Long term phase IV studies examining the establishment of a strong humoral immune response and the maintenance of immunological memory are ultimately the only way we will understand the potency of these different vaccine formulations, and their value to our long-term protection from SARS-CoV-2. 

FlowMetric Life Sciences is actively supporting clinical trials for vaccine development by providing high complexity flow cytometry analysis, serology testing of antibody-titers, along with Isoplexis-based functional proteomic solutions for precision immuno-profiling. To learn more, please contact one of our business development team members today.

References:

Raphael, I. et. al. (2020) Memory CD4+ T-cell in immunity and autoimmune disease. Cells 9(3) 531. https://doi.org/10.3390/cells9030531

Chatenoud, L., et.al. (1990) In Vivo Cell Activation Following OKT3 Administration. Systemic Cytokine Release and Modulation by Corticosteroids. Transplantation. Apr;49(4):697-702. https://www.ncbi.nlm.nih.gov/pubmed/2109379

De Rosa, S. C. (2012) Vaccine Applications in Flow Cytometry. Methods Jul 57(3): 383-391. doi: 10.1016/j.ymeth.2012.01.001

Lees, J. R. & Farber, D. L. (2010) Generation, persistence and plasticidy of CD4 T-cell memories. Immunol. 130(4) 463-470.  doi: 10.1111/j.1365-2567.2010.03288.x

Jameson et. al. (2018) Understanding Subset Diversity in T Cell Memory. Immunity, 48(2):214-22

 

Authored by: Dr. Julie Bick

 

 


Dr. Julie Bick is a medicinal biochemist who has spent close to 7 years with FlowMetric Life Sciences. After receiving her doctorate in Biochemistry at Southampton University in the UK, she began her career as Associate Professor at Rutgers University, NJ, before moving to the west coast to perform biomedical research with Syngenta and Novartis at the Torrey Mesa Research Institute in San Diego. Dr. Bick specializes in biomedical engineering of cells and proteins in order to provide innovative therapeutic and diagnostic solutions. She brings to FlowMetric a clinical expertise across a wide range of therapeutic areas from autoimmunity to oncology and chronic inflammatory conditions, acquired over 25 years of research experience in academic, biotechnology and pharmaceutical laboratories. In leading FlowMetric Life Sciences’ innovation initiatives, Dr. Bick has been collaborating with BurstIQ to implement Block Chain solutions into the company’s Contract Research Organization division, with a focus on enhanced big data analytics and process control solutions in the regulated clinical environment. Dr. Bick is committed to working with local Community Colleges to support STEM programs for the next generation of scientists.

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