• No results found

Transcriptomic and functional investigations of glutenreactive CD4+ T cells


Academic year: 2023

Share "Transcriptomic and functional investigations of glutenreactive CD4+ T cells"


Laster.... (Se fulltekst nå)



Transcriptomic and functional investigations of gluten- reactive CD4+ T cells

Doctoral thesis by Łukasz Wyrożemski

K. G. Jebsen Coeliac Disease Research Centre Department of Immunology

Institute of Clinical Medicine Faculty of Medicine

University of Oslo 2023


© Łukasz Wyrożemski, 2023

Series of dissertations submitted to the Faculty of Medicine, University of Oslo

ISBN 978-82-348-0160-0

All rights reserved. No part of this publication may be

reproduced or transmitted, in any form or by any means, without permission.

Print production: Graphics Center, University of Oslo.



Table of contents

Acknowledgements 5

Abbreviations 6

List of papers 9

Introduction 10

1) The immune system 10

• Anatomical and physiological barriers 12

• The innate immune system 13

• The adaptive immune system 14 • T cells and B cells 14 • The T-cell receptor 15 • T-cell development 17 • T-cell activation 19 • CD4+ T-cell effector subsets 23 • CD4+ memory T cells 29 2) Coeliac disease 30

• Dietary gluten and immunodominant gluten epitopes 32

• Gluten-driven enteropathy of small intestine 33

• Gluten-reactive CD4+ T cells 36

• T cell-B cell collaboration in CeD 39 3) C-type lectin-like receptor CD161 40

• CD161-expressing T cells 41

• Lectin-like transcript 1 43

4) DNA-sequencing technologies 44 • Single-cell RNA-sequencing 46 • Smart-seq2 49 • Bioinformatic analysis of scRNA-seq data 53 Aims of thesis 56

Summary of papers 57

Methodological considerations 61



• Coeliac disease patients (paper I, II and III) 61

• Cell isolation, tetramer staining and cell enrichment (paper I, II and III) 62

• Flow cytometry and Fluorescence activated cell sorting (paper I, II and III) 63 • Preparation of scRNA-seq libraries (paper I, II and III) 65 • Sequencing and transcriptome analysis (paper I and II) 66 • T-cell stimulation assays (paper III) 69 • Cytokine measurements (paper III) 72 • T-cell proliferation assays (paper III) 72 • Anti-CD161 monoclonal antibodies and ligation of CD161 (paper III) 73

Discussion 75

• Examination of index switching (paper I) 75

• Analysis of gluten-reactive CD4+ T cells by scRNA-seq (paper II) 77

• Investigation of CD161 in gluten-reactive CD4+ T cells (paper III) 79

• The role of CD161 in CD4+ T cells (paper IV) 81

Conclusions and future perspectives 83 References 86




First of all, I would like to acknowledge my main supervisor, Shuo-Wang Qiao, for her support. Secondly, I would like to thank my co-supervisor, Ludvig M. Sollid as well as member of his group. Especially I would like to thank Marie and Bjørg for their technical assistance in many occasions. I am also thankful to members of my own group, Asima and Ying, for their help. Most of all, I am grateful to my wife, Agata, who supported me for the whole time.

Dziekuję moim rodzicom, dziadkom oraz przyjaciołom za pomoc i wsparcie podczas doktoratu.

Łukasz Wyrożemski, Oslo, July 2022




APC antigen presenting cell BCR B-cell receptor

B-LCL B lymphoblastoid cell line

bp base pair

CCR C-C motif chemokine receptor (e.g. CCR9) CD cluster of differentiation (e.g. CD4)

CDR complementarity-determining region CeD coeliac disease

CLEC2D C-type lectin domain family 2 member D CXCL chemokine (C-X-C motif) ligand (e.g. CXCL13) CXCR chemokine (C-X-C motif) receptor (CXCR5) CyTOF cytometry by time of flight

DAMP damage-associated molecular pattern DC dendritic cell

DEG differentially expressed gene DGPs deamidated gluten peptides dNTPs deoxynucleoside triphosphates cDNA complementary DNA

EBV Epstein-Barr virus ExAmp exclusion amplification

FACS fluorescence-activated cell sorting FOXP3 forkhead transcription factor 3 GSEA gene set enrichment analysis HLA human leukocyte antigen IELs intraepithelial lymphocytes IFN interferon (e.g. IFN-γ) IL interleukin (e.g. IL-4)

ITAM immunoreceptor tyrosine-based activation motif ITIM immunoreceptor tyrosine-based inhibition motif iTREG induced TREG



KLRB1 killer cell lectin-like receptor subfamily B member 1 Lck lymphocyte-specific protein tyrosine kinase

LLT1 lectin-like transcript 1

LPLs lamina propria lymphocytes LPS lipopolysaccharide

mAb monoclonal antibody

MAIT mucosal associated invariant T cells MHC major histocompatibility complex

MICA MHC class I polypeptide-related sequence A MMLV moloney murine leukemia virus

mRNA messenger RNA

MR1 MHC-related molecule 1 NK natural killer cell

NKRP1A natural killer receptor protein 1A nTREG natural TREG

PAMP pathogen-associated molecular pattern PBMC peripheral blood mononuclear cell PCA principal component analysis PCR polymerase chain reaction PMA phorbol 12-myristate 13-acetate PHA phytohaemagglutinin

pMHC peptide-MHC complex PRR pattern recognition receptor RNA-seq RNA sequencing

ROR2C retinoic acid-related orphan receptor variant 2 RT-qPCR real-time quantitative polymerase chain reaction scRNA-seq single-cell RNA sequencing

SMART switching mechanism at the end of the 5'-end of the RNA transcript SNP single-nucleotide polymorphism

SLO secondary lymphoid organ

STAT signal transducer and activator of transcription (e.g. STAT4)



T-bet T-box transcription factor TCC T-cell clone

TCeD treated coeliac disease TCM T central memory TCR T-cell receptor TEM T effector memory TFH T follicular helper cell

TGF transforming growth factor (e.g. TGF-β) TG2 transglutaminase 2

TH T helper cell (e.g. TH1) TLR toll-like receptor

TPH T peripheral helper cells TREG T regulatory cell

TRM T tissue-resident memory

tSNE t-distributed stochastic neighbour embedding TSO template switch oligonucleotide

UCeD untreated coeliac disease

UMAP uniform manifold approximation and projection UMIs unique molecular identifiers



List of papers

Paper I

Yao Y, Zia A, Wyrożemski Ł, Lindeman I, et al. 2018. Exploiting antigen receptor information to quantify index switching in single-cell transcriptome sequencing experiments. PLoS ONE. 13: e0208484.

Paper II

Yao Y, Wyrożemski Ł, Lundin KE, et al. 2021. Differential expression profile of gluten-specific T cells identified by single-cell RNA-seq. PLoS One. 16: e0258029.

Paper III

Wyrożemski Ł, Sollid LM, Qiao SW. 2021. C-type lectin-like CD161 is not a co- signalling receptor in gluten-reactive CD4+ T cells. Scand J Immunol. 93: e13016.

Paper IV

Wyrożemski Ł, Qiao SW. 2021. Immunobiology and conflicting roles of the human CD161 receptor in T cells. Scand J Immunol. 94: e13090.




1) The immune system

The immune system is a complex network of organs and cells with the purpose to protect the host from pathogens and other environmental challenges. The fully integrated immune response is multilayered and uses various mechanisms to tailor its actions. Undoubtedly, the most fundamental role of the immune response is the detection of foreign structural features that allows to discriminate pathogen from the host. Such distinction is essential to effectively eliminate the danger without causing extensive self-damage to own body tissues (Chaplin, 2010; Marshall et al., 2018).

The immune system can be divided into two general categories based on the mode of recognition of foreign pathogenic structures, namely the innate immune system and the adaptive immune system. Historically, the innate and adaptive immune responses were believed to act independently where the innate immunity constitutes the first line of defense while the adaptive immunity is being activated at the later stage in order to clear the infection and provide long-term immunological memory. This view has changed. Although both arms of the immune system are fundamentally different in their mechanisms of action, the synergy between the two is essential for effective and well-regulated immune response. Importantly, the adaptive immune system requires innate signals for its activation. In this way, the adaptive immune system takes advantage of the innate immune system’s ability to discriminate between dangerous threats and less significant or even beneficial factors (Chaplin, 2010; Marshall et al., 2018).

Innate immunity is evolutionarily ancient component of host defense and is present in all multicellular organisms. Adaptive immunity is a more recent evolutionary invention and is found in jawed fish and higher vertebrates. Adaptive immunity has



developed to function in the context of the already existing innate immune system.

The interdependence of innate and adaptive parts of immune response could be illustrated by antigen-presenting cells (APCs) of the innate immune system, for example dendritic cells (DCs), that present antigens to cells of the adaptive immune system. Therefore, it is sometimes impossible to draw a clear demarcation line and separate those two integral components of the immune system (Turvey & Broide, 2010). However, for the purpose of brief introduction to this complex issue I will simplistically divide the immune system into three layers: (1) anatomical and physiological barriers, (2) the innate immune system and (3) the adaptive immune system (Figure 1).



Figure 1. The human immune system. The human immune system can be divided into three categories:

(1) anatomical and physiologic barriers, (2) innate immunity and (3) adaptive immunity. Anatomical and physical barriers represent the first line of defense to most pathogens. Innate immunity is an important part of human immune system that provides critical tools for rapid sensing and clearing of pathogens. Adaptive immunity constitutes much broader and finely tuned mechanisms for the elimination of danger. The ongoing interaction between those three components is necessary to provide vital immunity and maintain host immune homeostasis.

Adapted from Turvey & Broide, 2010 with permission.

Anatomical and physiological barriers

Physical barriers represent a considerable obstacle to most infectious agents (Figure 1). Those barriers include 1) skin, 2) epithelial cell lining in the upper respiratory tract, lower respiratory tract and gastrointestinal tract, 3) low pH in the stomach and 4) various secretions such as bacteriolytic lysozyme in tears and saliva. The importance of physical barriers can be observed in patients with severe skin burns where innate and adaptive immune mechanisms are incapable to compensate for the lack of intact skin barrier (Turvey & Broide, 2010).



The innate immune system

Innate immunity relies on a limited number of invariant receptors recognising conserved structural components that are shared by diverse groups of pathogens.

The innate response acts rapidly after encountering an invading pathogen and generates a protective inflammatory response within minutes of invasion. Cellular component of innate immunity includes macrophages, DCs, mast cells, neutrophils, eosinophils and natural killer (NK) cells. To augment cellular responses, the innate immune system also uses humoral elements involving soluble proteins and bioactive molecules such as complement proteins, lipopolysaccharide (LPS) binding protein, C-reactive protein, collectins and antimicrobial peptides such as defensins (Figure 1) (Turvey & Broide, 2010).

Generally, there are three innate strategies to recognise invading pathogens. The first strategy is to recognise conserved molecular structures, collectively termed as pathogen-associated molecular patterns (PAMPs), inclusive of LPS from gram- negative bacteria, bacterial flagellar proteins, viral double-stranded RNA or unmethylated DNA with CpG motifs characteristic of microbial DNA. PAMPs are recognised by receptors designated as pattern recognition receptors (PRRs). One important class of PRRs is the Toll-like receptors (TLRs). TLRs are found predominantly on neutrophils, eosinophils, epithelial cells and keratinocytes, and induce effector immune responses upon binding. Collectively, TLRs can identify a wide repertoire of conserved structures such as LPS (TLR4), flagellin (TLR5) or lipoproteins (TLR1, TLR2, TLR6). The second approach used by the innate immune system is to sense danger signals in the form of damage-associated molecular patterns (DAMPs). DAMPs represent molecules released by injured cells or damaged body tissues. DAMPs are recognised by NOD-like receptors which drive the immune response through the formation of an inflammasome, a multiprotein complex that activates pro-inflammatory cytokines interleukin (IL)-1b and IL-18. The third strategy occurs through recognition of “missing self”. There, receptors on



innate immune cells detect molecules that are expressed by healthy cells, but are lost on aberrant cells, for example infected cells or cancer cells. In healthy situation, these molecules deliver inhibitory signals that prevent the activation of the innate immune response. On the other hand, aberrant cells downregulate surface expression of these molecules leading to effector response from the innate immune cells. Classical example of such situation is the downregulation of major histocompatibility complex (MHC) class I proteins that results in the activation of NK cells and subsequent cytolytic activity (Turvey & Broide, 2010). Collectively, although the innate immune system responds very quickly to any dangerous signals indicating infections, it cannot build and maintain immunological memory to prevent reinfections.

The adaptive immune system

The adaptive immune system has evolved in order to provide broad immunological protection against a vast array of potential threats. The two most important properties of adaptive immunity are (i) large repertoire of receptors generated through somatic recombination and (ii) immunological memory that is generated after first encounter with an antigen. Adaptive immunity can be divided into cellular and humoral components (Figure 1). Cellular component relies on T lymphocytes, which mature in the thymus, and B lymphocytes which mature in the bone marrow.

Humoral component is mediated by antibodies produced by plasma cells that develop from activated B cells (Bonilla & Oettgen, 2010).

T cells and B cells

T cells as well as B cells are formed in the primary lymphoid organs (thymus and bone marrow) and subsequently traffic to secondary lymphoid organs (SLOs; lymph



nodes and spleen) where they encounter antigens. Activated lymphocytes exiting from SLOs migrate to sites of infection or inflammation with the purpose of exerting effector functions. This migration is regulated by various homing receptors, for example the integrin α4β7 facilitates homing to the gastrointestinal tract by binding to MadCAM-1 molecule located on gut endothelial cells. T cells and B cells proliferate after antigen recognition in order to reach sufficient number and mount effective immune response. The first exposure to an antigen (the primary response) is relatively slow and leads to production of antigen-specific antibodies as well as to generation of memory cells. If exposed to the same antigen (the secondary response), memory cells display rapid effector functions and protective immune response is quickly established (Bonilla & Oettgen, 2010). Although adaptive immune response is shaped by a synchronised interplay of various subsets of APCs, T cells and B cells, the following chapters will focus on CD4+ T-cell biology.

The T-cell receptor

The T-cell receptor (TCR) is a heterodimer composed of two disulphide-linked polypeptide chains. Each TCR is composed of variable domain and constant domain followed by a membrane-spanning region and a short cytoplasmic tail. The TCR loci contains a series of variable (V), diversity (D), joining (J) and constant (C) gene segments. V, J and C gene segments are present in all TCR loci (α, β, γ, δ) while only β and δ loci contain additional D segments. During spatially and sequentially ordered process of V(D)J recombination, single V, D and J segments are randomly spliced together to form V-(D)-J cassette that represents one of a vast number of possible permutations (Figure 2). V(D)J recombination, mediated by RAG1 and RAG2 proteins that constitute V(D)J recombinase, is either a single-step process for α and γ chains or two-step process for β and δ chains. Single-step process involves joining of V and J segments. On the other hand, two-step process begins with



joining of D and J segments followed by addition of V segment to the rearranged D-J cassette. Functional VJ or VDJ exons are eventually joined to C exon.

Combinatorial assembly of V-J cassette and V-D-J cassette during V(D)J recombination, where each segment was chosen from several available possibilities, represents a mechanism driving TCR diversity. The diversity of TCR antigen-binding domain is further amplified by the loss or gain of small number of nucleotides at the junctions between segments (Roth, 2014). Peptide-MHC (pMHC) complex is engaged by the TCR via three complementarity-determining region (CDR) loops located on each chain of the TCR. As a whole, six CDR loops form the antigen- binding site of the TCR. The variable CDR1 and CDR2 loops are germline-encoded within V gene segments, whereas the hypervariable CDR3 loop is formed during V(D)J recombination. CDR3 loops are therefore believed to be the main drivers of TCR specificity. The process of V(D)J recombination in humans can theoretically produce approximately 1018 different TCRs (Attaf et al., 2015).



Figure 2. V(D)J recombination and generation of TCRα, TCRβ, TCRγ and TCRδ chain transcripts. V(D)J recombination is either a single-step process for TCRα chain and TCRγ chain or two-step process for TCRβ chain and TCRδ chain. In a single-step process, V to J recombination brings together one T cell receptor variable (TRV) segment to one T cell receptor joining (TRJ) segment. In a two-step process, D to J recombination links together one T cell receptor diversity (TRD) segment one TRJ segment. Subsequently, V to DJ recombination links together rearranged DJ cluster to one TRV segment. After V(D)J recombination, the intervening sequences are spliced out in order to generate TCR transcripts where V, J and C segments (TCRα and TCRγ) or V, D, J and C segments (for TCRβ and TCRδ) are directly adjacent. (a) The human tra locus consists of 46 T cell receptor alpha variable (TRAV) segments followed by 51 T cell receptor alpha joining (TRAJ) segments and one T cell receptor alpha constant (TRAC) segment. (b) The human trb locus contains 48 T cell receptor beta variable (TRBV) segments followed by two TRBD-TRBJ-TRBC clusters composed of in total 2 T cell receptor beta diversity (TRBD) segments, 12 T cell receptor beta joining (TRBJ) segments and 2 T cell receptor beta constant (TRBC) segments. (c) The human trg locus is made of 6 T cell receptor gamma variable (TRGV) segments followed by two TRGJ-TRGC clusters composed of in total 5 T cell receptor gamma joining (TRGJ) segments and 2 T cell receptor gamma constant (TRGC) segments. (d) The human trd locus is embedded in tra locus and is comprised of 8 T cell receptor delta variable (TRDV) segments followed by 3 T cell receptor delta diversity (TRDD) segments and 4 T cell receptor delta joining (TRDJ) segments. Adapted from Attaf et al., 2015 with permission.

T-cell development

T cells originate from haematopoietic stem cells in the bone marrow. The progenitors of T cells, called thymocytes, migrate to the thymus where they undergo an auditioning for the ability to recognise self-peptides complexed with MHC molecules (self-pMHC). Thymocytes follow a program where they progress through three developmental stages, beginning with CD4-CD8- double-negative stage



followed by CD4+CD8+ double-positive stage and lastly CD4+CD8- or CD4-CD8+

single-positive stage. The process leading to surface expression of αβTCR generated during V(D)J recombination marks the transition from double-negative stage to double-positive stage. Subsequently, double-positive thymocytes are selected based on the strength of interaction between the TCR and self-pMHC molecules. Double-positive thymocytes that are non-responsive to self-pMHC are eliminated in a phase referred to as positive selection. Likewise, Double-positive thymocytes that are overly-responsive to self-pMHC are removed during so called negative selection. Only those double-positive thymocytes that recognise self- pMHC with intermediate strength are induced to differentiate into single-positive thymocytes. Ultimately, selection on MHC class I molecules will give rise to naïve CD8+ T cells while selection on MHC class II molecules will result in producing naïve CD4+ T cells. The repertoire of naïve T cells leaving the thymus and entering the periphery is self-tolerant, yet highly functional towards foreign antigens (Yates, 2014).

According to the clonal selection theory, each T cell bears TCR of a single specificity and theoretically recognise only one particular peptide antigen complexed with MHC. Such TCR has no affinity for the antigenic peptides alone and has very low affinity for MHC containing other antigens. However, this notion is being questioned as it was estimated that the number of potential antigens exceeds the number of available TCRs. In this way, T cells can provide comprehensive immune protection only if they are cross-reactive and thus are capable of recognising several potential antigens. Unfortunately, some cross-reactive T cells might be weakly self-reactive and cause autoimmune reaction during recognition of foreign peptides that strongly resemble epitopes contained in host proteins (Sewell, 2012).

Altogether, T cells that passed selection in the thymus join the pool of circulating T cells. αβTCR-expressing T cells (αβ T cells) are the most abundant population of T cells in peripheral blood and largely recognise peptide antigens complexed with



MHC. γδTCR-expressing T cells (γδ T cells) account for around 10% of circulating T cells, but are much more abundant in epithelial tissues. All T cells expressing TCR restricted to peptide antigens are considered conventional T cells. Conversely, unconventional T cells are those αβ T cells or γδ T cells that recognise non-peptide antigens, such as lipid antigens or bacterial metabolites, complexed with non- classical MHC molecules. The selection of thymocytes that give rise to unconventional T cells is scarcely understood, but is likely to mirror selection process of conventional T cells. An example of unconventional T cell population is mucosal associated invariant T (MAIT) cells that express semi-invariant αβTCR which recognises biosynthetic derivatives of riboflavin synthesis complexed with the non- classical MHC-related molecule 1 (MR1) (Attaf et al., 2015).

T-cell activation

αβ T cells are activated by the recognition of antigenic peptides presented on MHC molecules. MHC molecules (in humans referred to as human leukocyte antigens - HLAs) are cell surface glycoproteins that bind short peptide fragments. Peptides derived from endogenous proteins are presented on HLA class I molecules while peptides acquired from exogenous proteins that were ingested and proteolytically processed are presented on HLA class II molecules. Three major classes of HLA class I molecules can be distinguished, namely HLA-A, HLA-B and HLA-C. Likewise, three major classes of HLA class II molecules exist, designated as HLA-DR, HLA-DQ and HLA-DP. CD8+ T cells engage peptides complexed with MHC class I molecules that are expressed in all nucleated cells. CD4+ T cells recognise peptides presented on MHC class II molecules being expressed in APCs (Gaud et al., 2018). In short, APCs are a heterogenous group of immune cells that mediate the adaptive immune response by processing antigens and displaying them for recognition by T cells. As mentioned before, any nucleated cell can present endogenous antigens to CD8+ T



cells using the MHC class I pathway which may result in cytotoxic killing and elimination of the cell presenting antigen. However, only professional APCs such as DCs, macrophages and B cells, can present exogenous antigens to CD4+ T cells utilising the MHC class II pathway together with additional signals necessary for optimal T-cell activation that will be described later in this chapter. Professional APCs are present in large numbers in the skin and mucosal sites where they actively sample exogenous proteins mostly through the process of phagocytosis. When antigens are acquired, APCs migrate to regional lymph nodes where they interact with T cells. DCs are the most potent APCs due to their exclusive ability to prime naïve T cells. On the other hand, DCs, macrophages and B cells participate in the expansion of immune responses by stimulating memory T cells. Upon this interaction, APCs receive stimulatory signals that promote their own development and function (Eiz-Vesper & Schmetzer, 2020).

Engagement of the TCR by pMHC complex leads to the formation of an immunological synapse, employment of co-signalling receptors and the initiation of TCR signalling. The central part of an immunological synapse is composed of TCR- CD3 complex binding to the pMHC complex. The TCR has a modest intracellular domain which lacks signal-transducing potential. Instead, the TCR is noncovalently associated with the invariant CD3 proteins (CD3γε heterodimer, CD3γδ heterodimer and CD3ζζ homodimer) and forms TCR-CD3 complex. Additionally, CD4 or CD8 co-receptors stabilise the interaction between TCR-CD3 and pMHC by binding to the invariant domains of MHC class II or MHC class I, respectively. Within the immunological synapse, CD4 or CD8 recruit Lck tyrosine kinase to close proximity to TCR-CD3 complex with the intention of permitting the phosphorylation of tyrosine residues contained in immunoreceptor tyrosine-based activation motifs (ITAMs) located in the cytoplasmic tail of CD3. This phosphorylation event leads to the initiation of intracellular signalling during antigen-induced T-cell activation and



results in employment of a series of key transcription factors (Glatzová & Cebecauer, 2019). However, interaction of TCR-CD3 with pMHC complex provides incomplete signal for activation of naïve T cells and as such may result in an acquired state of T cell functional unresponsiveness known as T-cell anergy. Only collective engagement of TCR-CD3 together with signals from co-stimulatory and/or co- inhibitory receptors (jointly referred to as co-signalling receptors) and cytokine receptors can orchestrate synchronised expression of genes important for effective T-cell responses such as proliferation, migration or cytokine production (den Haan et al., 2014).

It is accepted that three components, here called signals, are necessary for an optimal activation of T cells (Figure 3). Antigen binding by the TCR represents signal 1. Signal 2 is delivered by co-signalling receptors that positively or negatively modulate TCR signalling. In the classical two-signal model, CD28 is the primary co- stimulatory molecule required for the activation of naïve CD4+ and naïve CD8+ T cells. CD28 binds to its ligand CD80 or CD86 that are expressed on the surface of APCs and these receptor-ligand interactions promote proper T-cell growth and survival. However, the two-signal model has evolved into a more complex regulatory system with the discovery of novel co-signalling receptors (Chen & Flies, 2013).

Therefore, the tidal model of co-signalling has been proposed in which the simple two-signal model was revisited to encompass the complex interconnection of other co-signalling receptors that play a role not only in T-cell activation, but also during different phases of T-cell existence. In the tidal model, at the incoming tide co- stimulatory receptors are abundant on naïve T cells and are dragging T cells into functional responsiveness. At peak tide, both co-stimulatory and co-inhibitory are expressed. T cells are at the peak of activation and are able to exert their unique roles in the given context. As the tide recedes, the expression of co-stimulatory receptors is replaced by the expression of co-inhibitory receptors leading to the suppression of T-cell activities (Zhu et al., 2011). Signal 3 is provided by cytokines



that act to a certain degree by promoting chromatin remodelling, thus maintaining transcription of genes needed for differentiation and various effector functions. The necessity of cytokine signalling during antigen-induced T-cell activation is especially important for naïve CD8+ T cells that fail to develop optimal effector responses, survive poorly and do not form memory population in the absence of signal 3 delivered by IL-12 or type I interferons (IFNs). Similar to naïve CD8+ T cells, naïve CD4+ T cells also require signal 3 for a productive response and it may be provided by IL-1 (Curtsinger & Mescher, 2010).

Figure 3. Antigen-specific and antigen-independent activation of T cells. Antigen-specific activation of T cells requires three signals. Signal 1 is delivered by the TCR that binds to cognate antigen presented on MHC molecules. Signal 2 is mediated by co-signalling molecules. In naïve T cells, primary co-signal is delivered by CD28 that interacts with B7 family of molecules expressed on APCs, namely CD80 or CD86.

Signal 3 is provided by cytokines that are necessary to develop strong effector functions and to establish protective memory population. Adapted and modified from Lee et al., 2020 with permission.



CD4+ T-cell effector subsets

In response to the recognition of cognate peptide antigen, naïve CD4+ T cells undergo clonal expansion during which they proliferate, differentiate and acquire specific effector functions as well as form long-lived population of memory cells. The differentiation pathway is influenced mostly by cytokine milieu that dictates the spectrum of cytokines produced by the resulting effector T cells. Remarkable diversity can be observed among effector T cells which are subdivided based on their cytokine profile and expression of transcription factors into five major categories, namely T helper (TH) 1 cells, TH2 cells, TH17 cells, T regulatory (TREG) cells and T follicular helper (TFH) cells (Figure 4) (Zhu & Paul, 2008).

The discovery of TH1 and TH2 subsets has provided the first insight into the diversity of CD4+ T cells (Mosmann et al., 1986). TH1 cells are characterised by their capacity to produce IFN-γ and differentiate from naïve precursors in the presence of IL-12.

The master regulators of TH1 differentiation are T-box transcription factor (T-bet) and signal transducer and activator of transcription (STAT) 4 (Szabo et al., 2000). Early reports also suggested that IL-12 receptor (IL-12R) β2 subunit (Rogge et al., 1997) as well as CXC chemokine receptor (CXCR) 3 and C-C motif chemokine receptor (CCR) 5 were preferentially linked to TH1 phenotype (Bonecchi et al., 1998; Sallusto et al., 1998). TH1 cells are generally considered to play a role in eliminating intracellular pathogens and are associated with some autoimmune diseases (Luckheeram et al., 2012). TH2 cells can be distinguish by the ability to produce IL-4 and IL-13. They develop from naïve T cells under the influence of IL-4, GATA-3 transcription factor and STAT6 (Zheng & Flavell, 1997). In contrast to TH1 cells, TH2 cells preferentially express CCR3 and CCR4 (Bonecchi et al., 1998; Sallusto et al., 1998). TH2 cells mount immune response against extracellular pathogens as well as play a major role in allergic diseases and asthma (Luckheeram et al., 2012).



The classical separation of CD4+ T cells into two dominant effector subsets was changed by the discovery of TH17 cells that constitute a third major CD4+ T-cell lineage (Park et al., 2005; Harrington et al., 2005). The polarising conditions necessary for differentiation of naïve T cells into TH17 cells include IL-6 and transforming growth factor-β (TGF-β) while IL-23 is important in the expansion and survival of lineage-committed TH17 cells (Chen et al., 2007). T-bet and GATA-3 transcription factors are not required for TH17 differentiation. Instead, retinoic acid- related orphan receptor variant 2 (RORC2) transcription factor was identified as the master regulator and STAT3 as the major signal transducer for TH17 lineage (Crome et al., 2009). Moreover, TH17 cells do not produce signature cytokines of TH1 and TH2 lineages, but can be distinguished by production of IL-17, mainly proinflammatory IL-17A and IL-17F, as well as selective expression of CCR6 and IL- 23R. Additionally, TH17 cells display high levels of CCR4 and CCR5 (Annunziato et al., 2007). TH17 cells are responsible for host defence against extracellular bacteria and fungi. In addition, they are implicated in some autoimmune diseases (Crome et al., 2010).

TREG cells constitute the subset of CD4+ T cells that is involved in maintaining immune homeostasis, regulating immune responses and preventing autoimmunity.

TREG cells can be phenotypically characterised by the constitutive expression of CD25 (IL-2R α chain) and forkhead transcription factor 3 (FOXP3) (Yagi et al., 2004).

There are two major subsets of TREG cells. Natural TREG (nTREG) develop in thymus whereas induced TREG (iTREG) arise in the periphery from CD4+FOXP3- conventional T cells. TREG suppress the activation/proliferation of other T cells via various mechanisms that include cell-to-cell contact or contact-independent mechanisms such as secretion of inhibitory cytokines TGF-β, IL-10 and IL-35 (Vignali et al., 2008).

TFH cells constitute the fifth major category of CD4+ T cells. TFH cells are considered the dominant providers of T-cell help to B cells and are often identified by high expression of CXCR5 that is necessary for migration into follicles of secondary



lymphoid organs (Breitfeld et al., 2000; Schaerli et al., 2000). CXCR5 is a chemokine receptor that, besides TFH cells, is also expressed by B cells and detects the chemokine CXCL13 which helps to recruit CXCR5-expressing B cells and TFH cells to lymphoid follicles (Legler et al., 1998; Hardtke et al., 2005). The differentiation of naïve T cells to TFH cells is regulated by IL-6, IL-21 and STAT3 signal transducer (Nurieva et al., 2008) together with TFH master regulator transcription factor Bcl6 (Nurieva et al., 2009; Johnston et al., 2009). The primary function of TFH cells is to support B cell maturation, thus facilitating antibody responses during infections. TFH

cells help to B cells is based on contact-dependent receptor-ligand interactions mediated, among others, by CD40L-CD40 pair together with secretion of IL-21 and chemoattractant CXCL13 (Crotty, 2014). IL-21 is particularly important as it promotes B cell proliferation in germinal centres and its further differentiation into plasma cells (Kuchen et al., 2007).

In addition to five major classes of CD4+ T cells, other putative lineages were identified such as T peripheral helper cells (TPH) and TH22 cells. TPH cells were characterised as T cells that drive B-cell responses in peripheral tissues. TPH cells are phenotypically similar to TFH cells except being negative for CXCR5 and transcription factor Bcl6. Like TFH cells, TPH cells also secrete CXCL13 as well as IL-21.

Unlike TFH cells, TPH cells express various inflammatory chemokine receptors that are involved in T-cell migration to sites of peripheral inflammation (Rao, 2018). TPH cells were found in multiple autoimmune conditions. They were abundant in synovial samples from seropositive rheumatoid arthritis patients and could be found in the circulation of RA patients albeit at much lower frequencies (Rao et al., 2017).

Furthermore, cells with similar phenotype were identified in the peripheral blood and gut of coeliac disease (CeD) patients. Finally, TPH cells were also present in patients with systemic sclerosis and systemic lupus erythematosus (Christophersen et al., 2019a). TH22 cells might constitute novel lineage that is unique in secretion of IL-22. IL-22, a cytokine strongly connected with TH17 cells, was found to be



produced by a subset of memory cells that coexpressed CCR6 together with skin- homing CCR4 and CCR10. However, these CD4+CCR6+CCR4+CCR10+ T cells did not produce IL-17 and thus might be representative of a separate TH22 lineage (Trifari et al., 2009). TH22 cells were shown to be enriched in the skin of patients with psoriasis, atopic eczema and allergic contact dermatitis (Eyerich et al., 2009).

Ever since the initial proof that CD4+ T cells can be divided into classes upon the pattern of produced cytokines, the concept of distinct CD4+ lineages that secrete unique sets of cytokines has been the archetype for how to classify differentiated TH

cells into effector subsets (O’Shea & Paul, 2010). Nonetheless, the monolithic view of separate CD4+ lineages has been challenged by the observation that in vitro differentiated CD4+ T cells can alter the range of produced cytokines upon culture conditions. For example, it was shown that culture of naïve T cells in the presence of TGF-β and IL-4 can give rise to IL-9-producing T cells that could represent distinct TH9 lineage. However, TGF-β can also reprogram TH2 cells to lose their lineage- specific characteristics, including expression of GATA-3, and switch toward production of IL-9 and TH9 phenotype (Veldhoen et al., 2008). Moreover, TH17 cells can acquire the capacity to produce IFN-γ alongside IL-17. TH1-like qualities of TH17 cells were based on availability of IL-12 and upregulation of transcription factors RORC2, T-bet and Runx1 (Wang et al., 2014). The alteration in transcriptional program together with proper environmental conditions are thus necessary to induce plasticity in phenotypic and functional behaviour. The plasticity of TH17 cells is particularly important as they have been linked to pathogenesis of diseases such as juvenile inflammatory arthritis, where the majority of synovial CD4+ T cells are TH1-like TH17 cells. The enrichment of TH1-like TH17 cells might be promoted by permissive cytokine milieu in the chronically inflamed joints that enables TH17 plasticity and drives subsequent lineage conversion (Nistala et al., 2010). On the whole, growing complexity of TH lineages may lead to revision of the current view of



TH lineage commitment to include the flexibility in cytokine production and dynamic expression of transcription factors as illustrated in Figure 4.



Figure 4. Differentiation of naïve T cells into effector subsets. (a) The classical view of naïve CD4+

T cell differentiation into one of five major effector CD4+ T cell subsets is dependent on lineage-defining transcription factors operating together with lineage-specific cytokine milieu (not shown). Different effector T- cell subsets were believed to represent stable lineages with inflexible lineage-defining cytokine profile. (b) Some effector CD4+ T cells can alter their cytokine profile and therefore display some degree of plasticity. The plasticity of effector CD4+ T-cell phenotype may reflect the response to dynamic environmental conditions and is likely dependent on transient changes in expression of crucial transcription factors. Adapted from O’Shea &

Paul, 2010 with permission.



CD4+ memory T cells

Following antigen-driven activation during infection, antigen-specific naïve CD4+ T cells proliferate and differentiate into effector subsets, a phenomenon referred to as clonal expansion. Once the infection is cleared, the majority of effector cells die during clonal contraction phase. However, a residual population of long-lived memory cells remains to establish defences against reinfections (Pepper & Jenkins, 2011). The majority of memory T cells is formed during primary infections in childhood. During this memory generation phase individuals are most susceptible to various infections. Once memory is established, individuals enter the memory homeostasis phase that spans throughout adulthood and is characterised by fairly stable memory T-cell frequencies and lower susceptibility to infections. Finally, the proportions and the functionality of memory T cells decreases in old age. This stage, referred to as immunosenescence, is marked by increased vulnerability to infections that is coupled with general physiological decline (Farber et al., 2014).

Isoforms of phosphatase CD45 is often used to distinguish naïve T cells from memory T cells. Naïve T cells are characterised by isoform CD45RA while any T cell expressing isoform CD45RO is regarded as memory cell (Mackay et al., 1999).

CD45RO+ memory T cells have been classically divided into T central memory (TCM) cells and T effector memory (TEM) cells. TCM circulate between blood and SLOs while TEM can migrate from blood to non-lymphoid tissues. T tissue-resident memory (TRM) cells comprise a third subset of memory T cells. TRM have limited migratory capacities and reside in mucosal and peripheral tissues like skin, lungs and intestinal mucosa (Nguyen et al., 2019). TCM express CD62L (L-selectin) and CCR7 which are involved in migration to SLOs. TCM lack immediate effector abilities, but can differentiate into TEM upon secondary stimulation. In contrast, TEM cells are negative for CD62L and CCR7, but express homing receptors that facilitate migration to non- lymphoid sites of inflammation. Moreover, TEM exhibit immediate effector functions and produce large amounts of cytokines within hours after stimulation (Sallusto et



al., 1999). TRM cells are tissue-resident, non-circulating population of memory cells that elicits in situ immune reaction to confer rapid protection. TRM cells exhibit characteristic features associated with tissue residence that include constitutive expression CD69, an otherwise marker for early activation, that in this context plays a role in TRM retention in tissues (Sathaliyawala et al., 2013; Kumar et al., 2017).

2) Coeliac disease

CeD is a chronic small intestinal immune-mediated enteropathy precipitated by exposure to dietary gluten in genetically predisposed individuals (Ludvigsson et al., 2013). CeD affects around 1-2% of Western population and occurs exclusively in genetically susceptible individuals. The great majority of CeD patients are HLA- DQ2.5-positive while HLA-DQ2.2 and HLA-DQ8 variants are less common among the patients. Gastrointestinal symptoms of CeD include harmful autoimmune reaction that causes structural alterations of the gut mucosa (Figure 5). Moreover, gastrointestinal manifestations of CeD are often accompanied by extraintestinal symptoms of which diarrhea, chronic abdominal pain, distended abdominal and weight loss are among the most common complications experienced by CeD patients. Life-long adherence to gluten-free diet is currently the only available treatment that can improve clinical symptoms of CeD and reverse gluten-driven damage of small intestinal mucosa (Figure 5). CeD is now considered a widespread public health problem due to substantial reduction in the quality of life of affected individuals (Lindfors et al., 2019).

CeD-associated HLA-DQ variants are the major risk factors predisposing to CeD. Yet, only a small fraction of individuals positive for HLA-DQ2.5, HLA-DQ2.2 or HLA-DQ8 develop the disease. Thus, it is likely that non-HLA genetic elements are required for the disease to develop (Withoff et al., 2016). Over 50 non-HLA candidate loci were identified to be associated with CeD, such as genes encoding interleukin receptors



(IL18R1 and IL18RAP), interleukins (IL12A, IL2 and IL21), chemokine receptors (CCR1, CCR2, CCR3 and CCR4) and co-signalling receptors (CD28, CTLA4 and ICOS) (van Heel et al., 2007; Dubois et al., 2010; Trynka et al., 2011; Gutierrez-Achury et al., 2015). The effect size of the non-HLA genes is generally very small. In addition to genes, environmental factors, for instance yet unknown intestinal insults that are able to induce danger signals in the gut, could contribute to CeD development (Withoff et al., 2016). The clinical diagnosis of CeD is based on serological testing and morphology assessment of biopsies collected from the upper small intestine.

HLA typing is often used to exclude the disease. Duodenal biopsy is considered burdensome both by the healthcare system and patients, thus efforts are being made to find less invasive diagnostic procedures (Sallese et al., 2020).

Figure 5. Ingestion of gluten causes selective destruction of intestinal epithelial cells in CeD individuals. CeD lesion develops over time, beginning as crypt hyperplasia (middle-left section) and eventually taking form of villous atrophy with crypt hyperplasia (middle-right and far-right panels). Strict and lifelong adherence to a gluten-free diet helps to revert gluten-induced damage of small intestine mucosa that slowly recovers and returns to normal morphology (far-left panel). Adapted from Lindfors et al., 2019 with permission.



Dietary gluten and immunodominant gluten epitopes

The term gluten is used to denote grain storage proteins rich in proline and glutamine that are present in wheat. However, gluten-like proteins with similar amino acid composition can be found in other cereals, that is secalins in rye, hordeins in barley and avenins in oats. Gluten, hordeins and secalins evoke strong immune response in CeD individuals. On the other hand, harmful immune reaction to avenins is uncommon and thus oats are considered safe for CeD patients. Wheat gluten represent a complex protein mixture of alcohol-soluble gliadins (α-gliadins, γ-gliadins and ω-gliadins) and alcohol-insoluble glutenins (high-molecular-weight glutenins and low-molecular-weight glutenins). Gliadins and glutenins are fairly resistant to enzymatic digestion in the gut lumen because of their high proline content. As a result, various long peptides ranging from 15 to 50 residues are generated. Subsequently, gluten peptides pass through the epithelial cell layer and enter the lamina propria where selected glutamine residues in “native” gluten peptides are deamidated by transglutaminase 2 (TG2). In consequence, glutamine residues are replaced by negatively charged glutamic acid, leading to generation of

“deamidated” gluten peptides that are characterised by increased binding affinity to the HLA-DQ2.5, HLA-DQ2.2 and HLA-DQ8 molecules (Sollid & Jabri, 2013).

Even though gluten contains many immunogenic peptides, of which the “33mer”

peptide from α-gliadin is considered the most immunogenic sequence, the T-cell responses to a handful of epitopes are observed across the great majority of CeD patients. These epitopes are widely known as immunodominant and six such epitopes have been defined so far. Five immunodominant epitopes are HLA-DQ2.5- restricted, namely DQ2.5-glia-α1, DQ2.5-glia-α2, DQ2.5-glia-ω1, DQ2.5-glia-ω2 and DQ2.5-hor-3. Among HLA-DQ8-restricted epitopes, DQ8-glia-α1 is regarded as immunodominant (Sollid et al., 2012; Sollid et al., 2020). The response to immunodominant epitopes was dominated by clonally expanded T cells over-using a biased TCR repertoire. V-gene bias towards TRBV7-2 (encoding TCR Vβ6.7 chain),



TRAV26-1 and TRAV4 was observed among DQ2.5-glia-α2-reactive CD4+ T cells.

TRBV7-2 and TRAV26-1 were also preferentially used as a pair (Qiao et al., 2011;

Qiao et al., 2014; Dahal-Koirala et al., 2016). Biased usage of TRAV12, TRAV4 and TRBV4 was found among DQ2.5-glia-ω2-reactive CD4+ T cells, but no preferential pairing was detected (Dahal-Koirala et al., 2016). For DQ8-glia-α1-reactive CD4+ T cells, the TCR repertoire was biased towards TRBV9 and TRAV26-2 (Broughton et al., 2012). It was speculated that the development of CeD might depend on the random generation of high-affinity TCRs recognizing particular immunodominant epitopes (Jabri & Sollid 2017).

Gluten-driven enteropathy of small intestine

The fundamental role of the gastrointestinal tract is to digest foodstuff, absorb nutrients and water, and eliminate undigested leftovers. The gastrointestinal tract is inhabited by a wide range of commensal microbes and is continually exposed to a multitude of antigens including dietary antigens. The gastrointestinal tract is usually divided into small intestine and large intestine. The small intestine can be further segregated into duodenum, jejunum and ileum whereas large intestine is made of caecum, colon and rectum. The small intestine and large intestine differ in size and mucosal architecture. The small intestine is a few meters long and is characterised by long and thin villi that provide extensive surface area of digestive/absorptive epithelium. On the other hand, the large intestine is wider in diameter but shorter than small intestine and is distinguished by flat surface without finger-like villi.

Therefore, the large intestine has little or no digestive abilities and is mainly involved in reabsorption of water. All parts of the intestine are constantly renewed by new epithelial cells arising from multipotent stem cells located near the bottom of the crypts (Mowat & Agace, 2014).



The intestinal mucosa is composed of intestinal epithelium, lamina propria and thin muscle layer underneath lamina propria. The intestinal epithelium is formed mostly by absorptive enterocytes. However, other cell types can also be found such as Paneth cells producing antimicrobial peptides and mucus-producing goblet cells.

The lamina propria is a loosely packed connective tissue that harbours the blood supply, lymph drainage system and mucosal nervous system. Interestingly, the gastrointestinal tract is also a home to large number of immune cells in the human body with T cells residing in both intestinal epithelium and lamina propria. The intestinal epithelium is populated by intraepithelial lymphocytes (IELs) that are located at the basal membrane between enterocytes. The great majority of IELs in small intestine are antigen-experienced CD8+ T cells that are heterogenous in phenotype, antigen specificity and function. IELs establish a protective immune barrier that helps to preserve the integrity of intestinal epithelium by eliminating infected epithelial cells and promoting epithelial repair. T cells residing in lamina propria are often referred to as lamina propria lymphocytes (LPLs). LPLs consist mainly of CD4+ T cells. Both IELs and LPLs display significant variation in population size and phenotypic composition that are dependent on the region of gastrointestinal tract (van Wijk & Cheroutre, 2009).

In CeD, ingestion of gluten results in the development of harmful mucosal autoimmune response in the upper small intestine. Increased number of inflammatory immune cells in intestinal epithelium and lamina propria, dysregulated overproduction of IL-15 as well as selective destruction of intestinal epithelial cells manifested in the form of villous atrophy (blunting or flattening of the villi) and crypt hyperplasia (elongation of the crypts) are clinical hallmarks of CeD (Figure 5) (van Bergen et al., 2015). IL-15, a cytokine upregulated in distressed intestinal epithelium, promotes the expression of NKG2D on the surface of IELs that is critical in licensing IELs to kill intestinal epithelial cells. NKG2D is a co-stimulatory C-type lectin-like receptor that, besides augmenting TCR-dependent responses, can also directly



induce cellular cytotoxicity independently of signalling via TCR. NKG2D interacts with MHC class I polypeptide-related sequence A (MICA) which in normal conditions is present only on a small percentage of enterocytes. However, MICA is a stress- induced molecule and significant increase of surface MICA is observed in inflamed small intestine of CeD individuals. The NKG2D-MICA interaction, supported by IL- 15, facilitates indiscriminate, TCR-independent killing of MICA-expressing enterocytes by NKG2D-positive IELs through perforin/granzyme B pathway that eventually leads to epithelial pathology typical of CeD (Hüe et al., 2004; Meresse et al., 2004). IELs in CeD inflamed intestinal environment likely undergo a shift in their genetic program. Reprogrammed IELs acquire an activated NK phenotype that is manifested by aberrant upregulation of multiple NK receptors, including aforementioned NKG2D as well as CD94/NKG2C, that render them capable of not only killing intestinal epithelial cells but also proliferating and producing inflammatory cytokines in an antigen-nonspecific, TCR-independent manner (Meresse et al., 2006). However, overproduction of IL-15 by epithelial cells was alone insufficient to fully activate IELs. The interplay between IL-15 and anti-gluten immunity was necessary for IELs to acquire a fully activated cytotoxic phenotype (Setty et al., 2015). Indeed, distinctive histological alterations together with expansion of IELs are accompanied by infiltration of gluten-reactive CD4+ T cells that constitute around 2% of all CD4+ T cells in CeD lamina propria (Bodd et al., 2013; Qiao et al., 2021). It remains unclear what exactly causes intestinal epithelial distress in CeD. Some studies suggested that gluten peptides might possess toxic properties that would induce overproduction of IL-15 and upregulation of stress- induced surface molecules in the small intestine of HLA-predisposed individuals.

Furthermore, anti-TG2 antibodies deposited in the small intestine mucosa of CeD patients might increase permeability of the epithelial barrier, thereby allowing gluten peptides to reach the lamina propria and subsequently affect local gut biology (Abadie et al., 2012).



Gluten-reactive CD4+ T cells

Gluten-reactive CD4+ T cells in peripheral blood and gut of CeD patients are effector memory cells (CD45RA-CD62L-CCR7-) with a narrow phenotype resembling that of TFH cells except being negative for CXCR5. These cells are CXCR3+CD39+CD161+, express co-stimulatory receptors CD28, ICOS and OX40 as well as co-inhibitory receptors PD-1 and CTLA-4. CD69 is expressed only by gluten-reactive CD4+ T cells isolated from the gut (Christophersen et al., 2019a). On the other hand, gluten-reactive CD4+ T cells isolated from peripheral blood express the proliferation marker Ki-67 (Christophersen et al., 2019a) and are positive for the gut-homing marker integrin α4β7 (Christophersen et al., 2014). The cytokine production by gluten-reactive CD4+ T cells is dominated by IFN-γ (Nilsen et al., 1995). In addition, some gluten-reactive CD4+ T cells also produce IL-21 (Bodd et al., 2010), IL-10, IL-4 (Christophersen et al., 2016) and IL-2 (Goel et al., 2019), but not IL-17 nor IL-22 (Bodd et al., 2010).

Numerous studies showed that HLA-DQ:gluten tetramer staining of peripheral blood gluten-reactive CD4+ T cells (in this paragraph referred to as tetramer test) is highly specific and sensitive in detection of CeD patients. Tetramer test could distinguish treated CeD (TCeD) patients from HLA-matched controls and individuals without CeD-predisposing HLA. This discrimination was possible after short oral gluten challenge that increased the frequency of gluten-reactive CD4+ T cells in the bloodstream of TCeD, but not control individuals, on day 6 after first gluten ingestion (Ráki et al., 2007). Moreover, tetramer test coupled with short oral gluten challenge was superior to the evaluation of histological deterioration that could be observed in some TCeD on day 4 after consuming gluten (Brottveit et al., 2011).

Tetramer test was also able to detect gluten-reactive CD4+ T cells in peripheral blood of both untreated CeD (UCeD) patients and TCeD patients without oral gluten challenge when combined with bead enrichment of gluten-reactive CD4+ T cells (Christophersen et al., 2014). Although only a few gluten-reactive CD4+ T cells could



be found in peripheral blood of healthy individuals carrying CeD-predisposing HLA- DQ2.5, those tetramer+ T cells differed from blood gluten-reactive CD4+ T cells from CeD patients by virtue of lower tetramer-binding intensity and no signs of biased TCR usage (Christophersen et al., 2016). All in all, tetramer test might supplement or perhaps replace the gold-standard histological examination of small bowel biopsies (Sarna et al., 2018a; Sarna et al., 2018b). Even though gluten-free diet normalises histology and disease-specific antibodies, gluten-reactive CD4+

memory T cells can still be detected in TCeD (Christophersen et al., 2014). Moreover, particular gluten-reactive CD4+ T-cell clonotypes, that is gluten-reactive CD4+ T cells expressing identical TCRα and/or TCRβ chains, persisted for decades in TCeD patients (Risnes et al., 2018). This indicates that even when on gluten-free diet, some TCeD patients experience a continuous low-level immune response that could arose from incidental/occasional exposure to gluten which in turn might have contributed to the maintenance of those specific clonotypes. As gluten-reactive CD4+ T cells are considered central in the pathogenesis of CeD (Figure 6), they represent an interesting target for potential therapeutic intervention (Christophersen et al., 2019b).



Figure 6. The role of gluten-reactive CD4+ T cells in CeD. Undigested gluten peptides enter the lamina propria where they are deamidated by TG2. In consequence, glutamine residues are replaced by negatively charged glutamic acid which increase the affinity of deamidated gluten peptides (DGPs) to the HLA- DQ2 and HLA-DQ8 molecules. DGPs are taken up by APCs, for instance dendritic cells, that present them to gluten-reactive CD4+ T cells. Also, both gluten-specific and TG2-specific B cells may act as APCs for gluten- reactive CD4+ T cells. Upon interaction, gluten-reactive CD4+ T cells proliferate and secrete distinctive cytokines, mainly IFN-γ and IL-21. Moreover, activated B cells differentiate into plasma cells that secrete antibodies against DGPs and TG2. Adapted from Lindfors et al., 2019 with permission.



T cell-B cell collaboration in CeD

In CeD, gluten-reactive CD4+ T cells might provide help to gluten-specific B cells as well as TG2-specific B cells and therefore promote their differentiation into plasma cells that secrete antibodies against DGPs and TG2, respectively (Figure 7). Both anti-DGP antibodies and anti-TG2 antibodies are hallmarks of CeD and are often used to diagnose CeD in the clinic (Jabri & Sollid, 2009). The occurrence of antibodies against TG2 in CeD patients consuming gluten is puzzling. The model explaining this conundrum is based on the fact that TG2 can form complexes with gluten peptides, thereby forming hapten-carrier-like structures. In this model, TG2- specific B cells take up TG2-gluten complexes through B cell receptor-mediated internalization. Subsequently, gluten peptides are presented on HLA-DQ molecules to gluten-reactive CD4+ T cells. As a result, TG2-specific B cells receive T-cell help that facilitates the production of anti-TG2 antibodies while simultaneously serving as APCs amplifying the T-cell responses against gluten (Figure 7) (Sollid et al., 1997).

The role of B cells as APCs for gluten-reactive CD4+ T cells is supported by the phenotype of the latter that closely resembles that of TFH cells which are considered the dominant providers of activation signals to B cells (Christophersen et al., 2019a).

Moreover, plasma cells were identified as the most abundant APCs displaying gluten peptides in the small intestine lamina propria of CeD patients (Høydahl et al., 2019). Complementary to this, gene expression profile of TG2-specific plasma cells from CeD small intestine biopsies indicated a possible cross-talk with CD4+ T cells due to the expression of HLA class II as well as CD86 that serves as the ligand for CD28 (Snir et al., 2019; Lindeman et al., 2021). On the whole, efficient collaboration between gluten-reactive CD4+ T cells and B-lineage cells appears to be important for the pathogenesis of CeD. Therefore, it was recently proposed that B cells could serve as main APCs for gluten-reactive CD4+ T cells in lymphoid structures whereas plasma cells might occupy similar role in nonlymphoid tissues. However, the ability



of plasma cells to stimulate CD4+ T cells is still to be demonstrated experimentally (Iversen & Sollid, 2020).

Figure 7. A hapten-carrier model explaining the occurrence of anti-transglutaminase 2 antibodies in CeD patients consuming gluten. TG2 can form covalently linked complexes with gluten peptides. Such TG2-gluten complexes can be bound by B-cell receptor (BCR) of TG2-specific B cells. The complexes are internalized and released gluten peptides are displayed on the HLA molecules to gluten-reactive CD4+ T cells. In this way, TG2-specific B cells act as antigen presenting cells for gluten-reactive CD4+ T cells that become activated, release cytokines and proliferate. In return, gluten-reactive CD4+ T cells provide help signals to TG2-specific B cells that differentiate into plasma cells secreting anti-TG2 antibodies. Adapted from Sollid et al., 1997 with permission.

3) C-type lectin-like receptor CD161

Human C-type lectin-like CD161, also known as Natural killer receptor protein 1A (NKRP1A), is expressed on the surface of various lymphocytes across innate and adaptive immune system (Fergusson et al., 2011). CD161 is present on almost all NK cells and approximately 25% of peripheral blood memory T cells inclusive of CD4+, CD8+, TCRαβ+ and TCRγδ+ cells (Lanier et al., 1994; Takahashi et al., 2006). CD161



was also reported on DCs while its expression on monocytes remains unclear (Poggi et al., 1997a; Llibre et al., 2016a). B cells do not express CD161 (Lanier et al., 1994;

Llibre et al., 2016a).

CD161 is encoded by Killer cell lectin-like receptor subfamily B member 1 (KLRB1) located within natural killer gene complex on chromosome 12 (Kirkham & Carlyle, 2014). CD161 is a type II transmembrane protein with N-terminal 38-amino acid cytoplasmic chain, 29-amino acid transmembrane segment and C-terminal 158- amino acid extracellular domain. It forms a disulfide-linked homodimer comprised of two subunits with a predicted molecular mass of 26 kDa each (Lanier et al., 1994).

C-terminal part of CD161 encompasses C-type lectin-like domain that is involved in the recognition and interaction with Lectin-like transcript 1 (LLT1) (Rozbeský et al., 2015). Cytoplasmic tail of CD161 either lacks any of the known signalling motifs (Aldemir et al., 2005) or contains noncanonical immunoreceptor tyrosine-based inhibition motif (ITIM) characterized by reduced inhibitory potential (Rosen et al., 2008). In T cells, CD161 was proposed to act as co-signalling receptor that augments TCR-dependent T-cell responses while CD161 located on NK cells operates purely as an inhibitory receptor. Unfortunately, the evidences for co-signalling abilities of CD161 in T cells are inconclusive (Llibre et al., 2016b) that is partially reflected in the general absence of decisive studies regarding protein structure of CD161 including the presence or absence of cytoplasmic signalling motifs.

CD161-expressing T cells

In adult peripheral blood, one distinct population among CD4+ T cells (CD161+) and two distinct populations among CD8+ T cells (CD161+ and CD161++) can be defined by the expression of CD161 (Figure 8) (Lanier et al., 1994; Takahashi et al., 2006). Both CD161-expressing CD4+ and CD8+ T cells are highly heterogeneous and encompass different T-cell lineages (Fergusson et al., 2011; Ussher et al., 2014;



Fergusson et al., 2016; Truong et al., 2019). Many studies utilized CD161 as marker of IL-17-producing T cells including TH17 cells and TC17 cells (Cosmi et al., 2008;

Maggi et al., 2010; Kleinschek et al., 2009; Bai et al., 2014; Bengsch et al., 2012;

Billerbeck et al., 2010). Surface CD161 was also associated with the subset of regulatory CD4+ T cells that produced IL-17, suppressed proliferation of conventional T cells (Pesenacker et al., 2013; Afzali et al., 2013) and displayed wound-healing potential (Povoleri et al., 2018). High CD161 expression was also ascribed to CD8+ MAIT cells that are defined by expression of IL-18R together with invariant TCRα chain Vα7.2-Jα33 and are restricted by MR1 molecule (Le Bourhis et al., 2010; Walker et al., 2012; Ussher et al., 2014; Fergusson et al., 2016).

Figure 8. Distribution of CD161 among CD8+ T cells and CD4+ T cells in peripheral blood of healthy individual. Two CD161-positive populations can be observed among circulating CD8+ T cells, namely CD161+CD8+ T cells defined by intermediate CD161 expression and CD161++CD8+ T cells with high CD161 expression. On the other hand, only one clear CD161-positive population exist among circulating CD4+

T cells and it is designated as CD161+CD4+ subset. Adapted from Fergusson et al., 2011 with permission.

Interestingly, T lymphocytes positive for CD161 were shown to display an innate-like response to IL-12 + IL-18 in TCR-independent manner and a shared transcriptional



Comparing CD4+ to CD8+ T cells, of the same tissue and age, re- vealed that genes upregulated in thymic CD4+ T cells were heavily involved in chromosome organization and cell

In this thesis, we have generated new recombinant HLA-DQ2.5-Streptag molecules that can be used as staining reagents of gluten-reactive CD4 + T cells in flow cytometry.. The quality

Through the herein presented work, we have addressed different aspects of the mechanistic basis and limitations of CD4 + T-cell induced macrophage tumor killing in a mouse model

In this study, we compared the gene expression pro- files of CD4 þ T cells obtained from untreated MS patients and healthy controls and did not observe differential gene

The cellular mechanism by which CD4 + T cells and tumor-infiltrating macrophages kill MOPC315 cells. Studies were facilitated by embedding MOPC315 cells in Matrigel, which

The unexpectedly modest changes in blood levels of IFN-  , a cytokine historically considered as the archetypical marker for activated gluten-specific CD4 + T cells (2),

In indicated synthetic ligand stimulation experiments and HIV-1 cell-to-cell transmission using HEK293T cells (cytokine analysis), CD4+ T cells were activated with activation

Our data indicate that phenotyping markers CD4, CD45RA, CD11c for the identification of CD4 + T cell subsets and myeloid dendritic cells, and p-p38, IkBa, p- cJun, p-NFkB, and CD86