1
Instituto Tecnológico y de Estudios Superiores de Monterrey
Campus Monterrey
School of Engineering and Sciences
Induction of antigen-independent T cell proliferation in vitro
A thesis presented by
Milena Ureña Herrera
Submitted to the
School of Engineering and Sciences
in partial fulfillment of the requirements for the degree of
Master of Science
In Biotechnology
Monterrey Nuevo León, June 11th, 2021
4
Dedication
To my loved family, specially, to my Dad. Thanks for all your unconditional confidence, support, patience, and encouragement. You were my main motivation for pushing through this work.
5
Acknowledgements
I would like to express my deepest gratitude to my lab friends Pedro Robles, Jose Antonio Cruz, Raul Piñeiro, César Ortiz, Javier Villela and Alejandro Robles; for all the help, teaching and support they gave me through these years.
To Dr. Marion Brunck, Dr. Eduardo Vázquez, and Dr. Cuauhtémoc Licona, for their guidance, knowledge, and patience.
To my all friends for their support and encouragement to obtain this degree.
To Tecnológico de Monterrey that supported me with tuition.
To CONACyT for my research scholarship CUV: 1019579.
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Induction of antigen-independent T cell proliferation in vitro by
Milena Ureña Herrera
Abstract
Innate immunity is the first line of defense of the body against pathogens and it responds in a nonspecific way to all threats. Some of its major responses are inflammation and antiviral defense, which overall help to prevent, control, and eliminate infections. It also allows the induction of an adaptive immune response, which is determinant to prevent re- infections. Adaptive immune response depends on antigen recognition, it triggers stimulation signals that In vivo induce T lymphocytes to proliferation response in addition to cytokine production and a modification to the pattern of expression of cell surface glycoproteins. T lymphocytes are one of the effector cells on the adaptive immune response. Their function of destroying the pathogens and their toxic molecules have made them popular for the development of cell therapies, for example, the CAR T cell therapies, which are based on modifying the antigen receptors of the T cells to allow them to detect and destroy cancer cells.
Therefore, mimic in vitro as much as possible in vivo stimulation to induce cell proliferation is key to improve cell therapy manufacturing, decrease the time of production and costs.
In this work, different stimulation protocols with PMA, ionomycin, IL-2, and Dynabeads™
were tested and evaluated in terms of proliferation induction, and progression in cell cycle, changes in the expression of surface proteins, and gene transcription levels of relevant genes. A correct overexpression of activation markers as well as cytokines transcription is confirmed, however, the stimuli were not correct to induce a significant increase in cell proliferation and contrary to expected, it seems that induced cells to apoptosis.
Keywords: T cell activation, antigen-independent, activation immunophenotype, proliferation
7
List of Figures
Figure 1. The immunological synapse 17
Figure 2. TCR-CD3 protein complex 18
Figure 3. Intracellular signaling cascade during T cell activation 19
Figure 4. CD28 and CTLA-4 ligands 24
Figure 5. Representative ancestry gating for CD69 and CD25 analysis 39 Figure 6. Representative ancestry gating for cell viability 40 Figure 7. Representative ancestry gating for apoptosis detection 41 Figure 8. Representative ancestry gating for CTLA-4 expression analysis 42 Figure 9. Proliferation kinetics over 6 days of primary cells. 47 Figure 10. Proliferation kinetics over 6 days of cell lines 49
Figure 11. Cell count of PBMCs after 6 days of stimulation with 100UI/mL IL-2 and/or
anti-CD3/anti-CD28 Dynabeads™ (1 bead/cell). 50
Figure 12. Expression of IL-2 and CTLA-4 in PBMCs and Jurkat cells 51 Figure 13. Stimulation index of extra and intracellular CTLA-4 52 Figure 14. Stimulation Index of CD69 and CD25 of viable CD3+ PBMCs 55 Figure 15. Stimulation Index of CD69 and CD25 of Jurkat cells 58
Figure 16.Proliferation kinetics over 6 days of human T cells stimulated with P. pastoris wasted supernatant without MRJP1 and 1, 10 or 100 ng/mL of MRJP1 66
8
List of Tables
Table 1. List of DAMPs and their receptors p.14
Table 2. A non-exhaustive list of various published protocols used for stimulation of human cells with antiCD3/anti CD28 beads, and their consequence on cell phenotype as measured in the
laboratory p.28
Table 3. A non-exhaustive list of various published protocols used for stimulation of human cells with PMA and Ionomycin, and their consequence on cell phenotype as measured in the laboratory
p.31 Table 4. Viable CD3+ PBMCs distribution according to the surface expression of CD69 and CD25 on unstimulated cells or stimulated cells with 10 ng/mL PMA and 1 µg/mL Io (Low PMA/Io) or 200
ng/mL PMA and 2 µg/mL Io (High PMA/Io) (N=2) p.53
Table 5. Viable CD3+ PBMCs distribution according to the surface expression of CD69 and CD25 on unstimulated cells or stimulated cells with 100 UI/mL IL-2 (N=1) and 100 UI/mL IL-2 +
Dynabeads™ p.54
Table 6. Viable Jurkat cells distribution according to the surface expression of CD69 and CD25 on unstimulated cells or stimulated cells with 10 ng/mL PMA and 1 µg/mL Io (Low PMA/Io) or 200
ng/mL PMA and 2 µg/mL Io (High PMA/Io) p.56
Table 7. Viable Jurkat cells distribution according to the surface expression of CD69 and CD25 on unstimulated cells or stimulated cells with 100 UI/mL IL-2 + Dynabeads™ p.57 Table 8. Distribution of PBMCs and Jurkat cells though the cell cycle according to the Dean-Jett Fox model before and after 24 h of stimulation with high PMA/Io p.59 Table 9. Apoptotic PBMCs and Jurkat cells before and after 24 h of stimulation p.58 Table 10. Summary of trialed methodologies for the optimization of T cell electroporation with
the Biorad Gene Pulser Xcell p.69
Table 11. Summary of trialed methodologies for the optimization of T cell lipofection with
Lipofectamine 3000 p.69
Table 12. Summary of trialed methodologies for the optimization of T cell electroporation with
Neon transfection system p.69
9
Abbreviations
Activation Protein 1 AP-1
Adhesion and Degranulation-Promoter Adapter Protein ADAP
Analysis of Variance ANOVA
Annexin V AnnV
Antigen presenting cells APCs
Ca2+ release-activated Ca2+ CRAC
Chimeric Antigen Receptor CAR
Concavalin A Con A
Cytotoxic T-Lymphocyte Antigen 4 CTLA-4
Damage Associated Molecular Patterns DAMPs
Diacylglycerol DAG
Endoplasmic Reticulum ER
Epidermal growth factor EGF
gamma interferon IFN-γ
growth factor receptor-bound protein 2 GRB2
Human Leucocyte Antigen HLA
Immune Synapse IS
inositol triphosphate IP3
Ionomycin Io
Linker of Active T cells LAT
Major Histocompatibility Complex MHC
Major Royal Jelly Proteins MRJPs
10
Median Fluorescence Intensity MFI
Mitogen-Activated Protein MAP
Nuclear Factor of Activated T cells NFAT
Pathogen Associated Molecular Patterns PAMPs
Pattern Recognition Receptors PRRs
Peripheral Blood Mononuclear Cells PBMCs
Phorbol 12-myristate 13-acetate PMA
phospholipase Cγ1 PLCγ1
Phytohemagglutinin PHA
Protein Kinase C PKC
Protein Tyrosine Kinases PTKs
Single Immunoreceptor Tyrosine Activation Motif ITAM
stimulation Index SI
Supramolecular Activation Cluster SMAC
T Cell Receptor TCR
Transcription Factors TF
Tumor Necrosis Factor TNF
11 Index
1. Chimeric Antigen Receptor T cells therapy ... 13
2. Overview of the immune system ... 15
2.1 Recognition of non-self by innate immune cells. ... 15
2.2 Recognition of non-self by adaptive immune cells. ... 18
2.3 The Immunological Synapse ... 19
2.4 Signaling cascade following antigen-dependent activation at the IS ... 20
2.5 Co-stimulation ... 23
2.6 Negative regulation through check point inhibitors ... 24
2.7 Responses of activation ... 26
3. Importance and application of studying activation-proliferation in vitro ... 27
3.1 In vitro antigen-independent activation methods ... 28
3.1.1 Antibodies ... 28
3.1.2 Lectins ... 31
3.1.3 PMA and Ionomycin ... 31
4. Continuous cell lines as models of primary cells... 34
5. Hypothesis and Objectives ... 34
5.1 Hypothesis ... 34
5.2 General Objective ... 34
5.3 Specific Objectives ... 35
6. Methodology ... 35
6.1 Cell Culture ... 35
6.2 PBMCs Isolation and T cell enrichment ... 35
6.3 Stimulation plating ... 36
6.4 Cell count analysis ... 38
6.5 Flow Cytometry ... 38
6.5.1 Staining ... 38
6.5.2 Gating and analysis ... 40
6.6 Gene transcription (RT-PCR) ... 44
7. Results ... 46
7.1 Specific Obj. 1: To investigate antigen-independent proliferation protocols previously described to increase human T cells proliferation in vitro ... 46
12 Specific Obj. 2: To confirm activation of stimulated human T cells using gene
transcription and flow cytometry ... 52
Specific Obj. 3: To assess changes in cell cycle progression of human T cells caused by stimulation applied ... 60
8. Discussion ... 62
9. Appendix ... 66
9.1 Alternative way to induce proliferation: MRJP1 ... 66
9.2 Optimization of T cell transfection ... 70
10. References ... 72
13
Chapter 1. Introduction
1. Chimeric Antigen Receptor T cells therapy
Cancer is a top global cause of death. A projection of cancer increase, based on the 2.7 million of cases on 2008 and on the Human Development Index, is for to 22.2 million cases by 2030 (Bray et al., 2012). It is supposed that cancer tissue acquired indispensable abilities to deal with immune mechanisms, as the ability to growth in an inflamed microenvironment, evasion of the immune system, mediated by tumor derived T regs, and to suppress immune reactivity (Cavallo et al., 2011). This allows the cancer cells to growth out of control. Advances in T cell biology and tumor immunology led to new approaches for therapies, as the Immune Checkpoint Blockade (ICB) therapies, which modulate the effector function of T cells in the tumor microenvironment, leading to the elimination of tumor and which have already led to durable remissions in many cancer patients (Hargadon et al., 2018; Thallinger et al., 2018). Other immunotherapies besides the ICB, consists in genetically reprogramming patients own immune cells so that they can find and attack cancer cells. These are named adoptive cell immunotherapies and an example of them are the Chimeric Antigen Receptor (CAR) T cells. CAR is selected according to the cancer that want to be attacked, since it must be specific for some surface molecule that cancer cells express. CD19 has become one of the most popular target, whose expression is restricted to B cells and their precursors, which are affected in B cell leukemia and lymphoma (J. X. Yu et al., 2019).
Some of these therapies have already been approved by the FDA and became a treatment option when the patient has followed their regular treatment scheme (chemotherapy, radiation, stem cell transplantation, among others) and has relapsed twice. They represent the patients' last hope for survival (Yescarta, 2020). In 2017, Yescarta (Axicabtagene ciloleucel) a CAR T cell therapy that targets CD19 was approved by FDA. This therapy is applied to patients with certain types of B cell lymphoma and has reported very promising results, with a 72% remission in patients (Yescarta, 2020*).
14 In a short-term follow-up, Yescarta is a cost-effective therapy for adults with relapse or refractory B cell lymphoma in comparison to salvage chemotherapy (Roth et al., 2018).
Nevertheless the cost of therapy is high, a single dose is around 373 000 USD, not including the expenses before and after the administration of it (Yescarta, 2020*).
The high cost of these therapies can be a limiting factor for patients. Another point to assess is the time manufacturer lasts to have a dose of CAR T cells ready to be administered to the patient. In the case of Yescarta, a median of 23 days from receipt of leukapheresesd sample at the manufacturing facility to return the CAR T cells to the clinical site, it’s been reported (Tyagarajan et al., 2020).
Data obtained from current clinical trials revealed that the cell culture and expansion time for most cases is up to 10 days; However, this period may vary between each patient and the specific time for cell expansion cannot be guaranteed. In some clinical studies culture times of more than 30 days have been reported. The concentration of cells per dose is very important for the success of these therapies, so the cells remain in culture until the required quantity is reached, which also varies according to each patient. For example, a standard dose for an adult is around 2 million cells per kilogram of body weight (Fritsche et al., 2020; Vormittag et al., 2018; Yescarta, 2020*).
In vivo T lymphocyte proliferation occurs in response to stimulation by antigen presenting cells (APCs). To replicate this process in vitro, as much as possible, it would be necessary to work with co-cultures of T lymphocytes and APCs. This implies extra complications for the expansion of the lymphocytes, making the process more cumbersome. To avoid the implementation of co-cultures with APCs, alternative in vitro stimulation methods have been developed (L. Chen & Flies, 2013; Levine, 2015), two of which are studied in this work, in order to develop an in vitro proliferation platform to study and optimize human T cell activation.
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Chapter 2. Literature Review 2. Overview of the immune system
The immune system in mammals is divided into innate (general) and adaptive (specialized) systems. Both systems work together and deal with different tasks. Innate immunity is the first line of defense of the body against pathogens and responds in a nonspecific way to all threats. It englobes body barriers as skin and mucosa, soluble molecules and specialized cells present in all individuals. Main effector cells of this system are phagocytes such as dendritic cells and neutrophils, natural killer cells, mast cells, eosinophils and basophils (Charles A. Janeway & Medzhitov, 2002). Major responses due to the innate immune system are inflammation and antiviral defense, which overall help to prevent, control, and eliminate infections (Takeuchi & Akira, 2010).
The induction of an adaptive immune response is determinant to prevent future re- infections, and it depends on antigen recognition and on key signals delivered by the innate immune system, such as the presence of inflammatory cytokines or dendritic cells expressing costimulatory signals and with a stopped antigen uptake (Ruslan Medzhitov
& Janeway Jr, 1998). The main function of the adaptive immune system is to destroy the pathogens and their toxic molecules and to generate an immunological memory, which is the development of lymphocytes with antigen-specific receptors on their surface. Major effector cells of the adaptive arm of the immune system are T and B lymphocytes (Alberts et al., 2002; Iwasaki & Medzhitov, 2004).
.
2.1 Recognition of non-self by innate immune cells.
To defend the body against external threats, the immune system must be able to discriminate between these external threats (non-self) and what it is part of the body (self).
Discrimination can take place thanks to the germline-encoded Pattern Recognition Receptors (PRRs) displayed on the surface of cells, which may or may not be the immune
16 system. These receptors recognize potential threats by binding to Pathogen Associated Molecular Patterns (PAMPs) on the surface of pathogens like bacteria and fungi (C. A.
Janeway, 1989). PAMPs can be lipids, carbohydrates, proteins, DNA and RNA.
Pathogens can be identified by various PAMPs. For example, viruses are recognized through their foreign nucleic acids and methylation patterns, bacteria display characteristic surface molecules such as peptidoglycans, flagellar protein and also characteristic methylation patterns, and fungi are recognized to zymosan and chitin molecules (Mogensen, 2009). Damaged and dying cells are recognized by Damage Associated Molecular Patterns (DAMPs), such as heparin sulfate, fibrinogen and Fibronectin (Roh & Sohn, 2018).
Table 1. List of DAMPs and their receptors. (Roh & Sohn, 2018)
Origin Major DAMPs Receptors
Extracellular matrix Biglycan TLR2, TLR4, NLRP3
Decorin TLR2, TLR4
Versican TLR2, TLR6, CD14 LMW hyaluronan TLR2, TLR4, NLRP3 Heparan sulfate TLR4
Fibronectin (EDA domain)
TLR4
Fibrinogen TLR4
Tenascin C TLR4
Intracellular compartments
Cytosol Uric acid NLRP3, P2X7
S100 proteins TLR2, TLR4, RAGE Heat shock
proteins
TLR2, TLR4, CD91
17
Origin Major DAMPs Receptors
ATP P2X7, P2Y2
F-actin DNGR-1
Cyclophilin A CD147
Aβ TLR2, NLRP1, NLRP3,
CD36, RAGE
Nuclear Histones TLR2, TLR4
HMGB1 TLR2, TLR4, RAGE
HMGN1 TLR4
IL-1α IL-1R
IL-33 ST2
SAP130 Mincle
DNA TLR9, AIM2
RNA TLR3, TLR7, TLR8,
RIG-I, MDA5
Mitochondria mtDNA TLR9
TFAM RAGE
Formyl peptide FPR1
mROS NLRP3
ER Calreticulin CD91
Granule Defensins TLR4
Cathelicidin (LL37) P2X7, FPR2
EDN TLR2
Granulysin TLR4
Syndecans TLR4
18
Origin Major DAMPs Receptors
Plasma membrane
Glypicans TLR4
2.2 Recognition of non-self by adaptive immune cells.
PRR such as TLRs are encoded in the germline, therefore the range of molecules that can be recognized is ultimately limited. In contrast, receptors on the surface of cells from the adaptive immune system have a much wider range of non-self-molecules, including pathogen molecules, they can recognize as foreign. This is because these receptors are encoded by genes that undergo somatic recombination, allowing for a greater diversity of patterns recognition, estimated in more than ten million of antigens (Akira et al., 2006).
Antigens can be molecules like proteins, polysaccharides, lipids or nucleic acids. These molecules could be originated within or outside of the body and each have differences in the regions that is recognized by the immune system (epitope) and therefore, the immune response induced may vary for each one (Abbas et al., 2017).
Antibodies are antigen binding glycoproteins produced by B cells. They are Y-shaped and belong to the immunoglobulin superfamily. The ends of this Y shape structure is specific for a particular epitope, allowing a precise bind between the two molecules. Soluble antibodies can neutralize or decrease the ability of pathogens to infect more cells.
However, antibodies also allow antibody-dependent cellular cytotoxicity. Membrane- bound antibodies, on the surface of B cells, act as antigen receptors which binding induce B cells to differentiate into plasma cells, able to secrete soluble antibodies specific for the recognized antigen (Abbas et al., 2017).
19 2.3 The Immunological Synapse
Figure 1. The immunological synapse (Huppa & Davis, 2003). Interaction between T cells and antigen presenting cells where antigen recognition, adhesion, and co- stimulation/checkpoint receptors come together.
T cells also have a specific antigen receptor, called the T Cell Receptor (TCR). This receptor only recognizes antigens coupled to a Major Histocompatibility Complex (MHC) molecule, and displayed by APCs, such as dendritic cells or macrophages. As MHC was studied and described using alloantibodies against leukocytes this complex usually referred as Human Leucocyte Antigen (HLA) system (Choo, 2007).
The contact between the complex antigen-HLA on the surface to the APC and the TCR on the surface of the T cell, forms a Supramolecular Activation Cluster (SMAC) or Immune Synapse (IS) (Figure 1). At this site, there is a rapid recruitment of additional signaling molecules such as costimulatory receptors, like CD28, or activation inhibitors like
(Valk et al., 2008). The IS also triggers the signaling pathway for Mitogen-Activated Protein (MAP) Kinases which ends up in a downstream activation of distinct Transcription Factors (TF). TFs bind to regulatory regions of genes and promote their transcription.
20 Some of these genes might be involved in T cell proliferation. During an immune reaction, the response to a specific antigen culminates in the clonal expansion of antigen-specific lymphocytes and this is a hallmark of the adaptative immune system. This proliferation is crucial to fight the infection or disease and once it is cleared, concentrations of T cells in the body return to their basal levels through a homeostasis feedback loop and only a few copies of specific memory T cells remain (Abbas et al., 2017; Dustin, 2014).
2.4 Signaling cascade following antigen-dependent activation at the IS
Figure 2. TCR-CD3 protein complex (Abbas et al., 2017). TCR heterodimers bind non- covalently with CD3, which serves as T cell co-receptor. TCR/CD3 complex is formed by four polypeptide chains assembled in 3 pair of dimers: εγ, εδ and ζζ.
The TCR is a heterodimer composed of two polypeptide chains, α and β or γ and δ, each containing a constant region anchored to the cell membrane and an extracellular variable region in charge of antigen binding. TCR heterodimers bind non-covalently with CD3, which serves as T cell co-receptor and is a characterizing element of cells from the T cell lineage. This TCR/CD3 complex is formed by four polypeptide chains assembled in 3 pair of dimers: εγ, εδ and ζζ. Peptides ε, γ and δ contain an extracellular immunoglobulin-like domain and a cytoplasmic domain with a single Immunoreceptor Tyrosine Activation Motif (ITAM) (Figure 2). CD3 ζ does not contain extracellular domain but its cytoplasmic domain
21 contains 3 ITAMs (Kane et al., 2000; Meuer et al., 1983). TCR-CD3 complex subunits lack intrinsic kinase activity so, downstream signal transduction depends on the recruitment and activation of Protein Tyrosine Kinases (PTKs). Upon binding its cognate antigen, the complex initiates a transduction signaling cascade with Src family kinase Lck.
It phosphorylates the tyrosine residues in ITAMS which induce a conformational change that creates a docking site for proteins like ζ-Asociated Protein of 70KDa (ZAP-70) (Klammt et al., 2015). In some cases, besides ZAP-70 activation, the second family member Syk, is catalytically activated by a combination of Src kinase-mediated trans- phosphorylation and auto-phosphorylation (Iwashima et al., 1994; Pitcher & van Oers, 2003)
Figure 3. Intracellular signaling cascade during T cell activation. Physiological activation signaling begins with antigen binding to TCR-CD3 complex and subsequent phosphorylation of ITAMs. Downstream activation events are induced by TCR
22 independent activation methods as PKC activation with PMA, an analog of DAG, or intracellular Ca2+ increased caused by Ionomycin, a calcium ionophore.
Activated ZAP and/or Syk phosphorylates the Linker of Active T cells (LAT), that binds then to phospholipase Cγ1 (PLCγ1), growth factor receptor-bound protein 2 (GRB2), VAV1, Nck, Adhesion and Degranulation-Promoter Adapter Protein (ADAP) and the related adaptor downstream of Shc. Shc recruits SH2 domain to binds to phosphorylated LAT. The signaling complex LAT-PLCγ1 hydrolyze the membrane phospholipid PIP2, obtaining the products inositol triphosphate (IP3) and Diacylglycerol (DAG) (Joseph et al., 2014).
IP3 binds to its receptor (IP3-R) on the Endoplasmic Reticulum (ER) to trigger the release of its calcium stores (krishna & Xiao, 2013). In addition, extracellular Ca2+ influx through Ca2+ release-activated Ca2+ (CRAC) channels across the plasma membrane increases Ca2+ intracellular concentration from ~50–100 nM Ca2+ to ~1 μM (Feske, 2007; Joseph et al., 2014; Lewis, 2001) . Ca2+ raise mitochondrial motility and its translocation with cytoskeletal dependent mechanisms. Mitochondria co-localization with CRAC channels, plus the redistribution with plasma membrane Ca2+ ATPase (PMCA) is key to maintain the high levels of Ca2+ for generalized activation of T cells. Sustained elevation of Ca2+
levels through CRAC channels allows T cell activation responses such as induced gene transcription, which leads to proliferation, differentiation, and cytokine production (Joseph et al., 2014).
On the other hand, DAG recruits RAS Guanyl Releasing Protein (RasGRP1) at the IS location at the cell membrane. Activated RasGRP1 allows the MAP Kinases ERK1/2 signaling. It increases the expression of the transcription factor c-Fos which dimerize with the transcription factor c-Jun, and formed the Activation Protein 1 (AP-1). AP-1 and Nuclear Factor of Activated T cells (NFAT) bind on the promoters of genes like IL-2 (Jain et al., 1992; Macián et al., 2001). DAG also recruits Protein Kinase C (PKC) θ by binding to its C1 domain, causing conformational change which allows kinase domain access for further activation. Besides this C1 domains, PKC-θ contains N-terminal C2-like domain
23 which is Ca2+ irresponsive. This structural difference allows PKC-θ to be activated by DAG or eventually a phorbol ester in Ca2+ independent manner (Brezar et al., 2015).
Protein Kinases regulate the biological activity of other proteins by phosphorylating them.
PKC is a widely conserved and large family of homologous serine/threonine protein kinases and PKC-θ is the first member recruited to the IS. Its signaling cascade results in the cell surface expression and/or function of some receptors like for insulin or Epidermal growth factor (EGF). PKC θ can be also recruited to the IS by CD28. CD28–PKC-θ complex formation and PKC-θ conformational change in this IS translocation is regulated by Lck tyrosine kinase, it serves as a linker/adaptor in CD28–PKC-θ complex in the most likely binding model trimolecular signaling complex: PKC-θ/Lck/CD28 (Brezar et al., 2015;
Isakov & Altman, 2012).
2.5 Co-stimulation
TCR engagement is not sufficient to induce full activation. Without costimulation, also referred to as a secondary signal, there is no efficient activation of the MAPK, PI3K/Akt, and IKK pathways. This produces a reduced AP-1 and NFkB activity, inconsistent transactivation of the CD28 response element (CD28RE) in the IL-2 promoter and induction of anergy (Wells, 2009). Anergy is a hyporesponsive state in which the cell does not respond to an immunogenic stimulus but remains alive. It is mainly characterized by an inhibition of proliferation and effector functions, and involves tyrosine kinase activation blocking, inhibition of calcium mobilization and IL-2r signaling blocking. (Schwartz, 2003).
Anergy could be classify into two categories. First, clonal anergy which is a consequence of an incomplete T cell activation, and anergy cause by adaptive tolerance, which is induced after the sustained antigen signaling and continuous cycles of proliferation and differentiation of cells (Schwartz, 2003).
At the molecular level, anergy is caused by proteins that prevent the induction of the IL-2 gene but are inactivated by signals from CD28 and/or the IL-2R, for example, the
24 transcriptional repressor Ikaros. Signaling through IL-2R transduces the signal for allowing T cells to progress beyond the anergic checkpoint, unblock the Ras/MAP kinase pathway and participate in an immune response. It is also reported that exogenous IL-2 can compensate for a lack of costimulation to avoid anergy (Schwartz, 2003; Wells, 2009).
CD28 on the surface of T cells interacts with B7-1 (CD80) and B7-2 (CD86) on the surface of the APC. These ligands on the surface of APCs promote T-cell proliferation, IL-2 production, cell survival via Bcl-xL transcription and prevents anergy (Boise et al., 1995).
The 2-signals model of T cell activation englobes CD28 signaling cascade as the primary costimulatory cascade for T cell activation, but subsequent investigations suggest a 3- signal model where the role of inflammatory cytokines, such as IL-12, is included, especially when antigen levels are low (Curtsinger et al., 2003).
2.6 Negative regulation through check point inhibitors
Signaling through CD28 also increases expression of CTLA-4 (or CD152) and PD-1 (or CD279) on the surface of T cells. CTLA-4 increased expression could be also caused by IL-2 signaling (Freeman et al., 2000; Walunas et al., 1996). Both, CTLA-4 and PD-1 are inhibitory receptors which are key in the peripheral T-cell tolerance and T-cell function (Fife & Bluestone, 2008). They help in the regulation of the cell response during stimulation, by limiting costimulatory signaling and others costimulatory molecules ligation (Linsley et al., 1991). It has also been reported that CTLA-4 and PD-1 transmit the initial T cell migratory stop signal, regulating the time and or/strength of the interaction between T cells and Dendritic cells (DC) (Rabenstein et al., 2014). Functional outcome of CTLA- 4 could be summarized as a raise in the threshold activation on T cells and the attenuation of clonal expansion; while the functional outcome of PD-1 could be summarized as the restriction of the function of effector T cells, mainly in nonlymphoid organs (Intlekofer &
Thompson, 2013).
25 Both CD28 and CTLA-4 bind to the same ligand but with different affinities (Figure 4).
CTLA-4 is almost 17 times more likely to bind than CD28 and that is why CTLA-4 ligation antagonizes early T-cell activation, leading to decreased IL-2 production inhibition of cell cycle progression, decreased cyclin expression, and modulation of TCR signaling.
Colligation of CTLA-4 with TCRs blocks the formation of ZAP-70-containing micro clusters in T cells (Rudd et al., 2009; Walunas et al., 1996). Approximately 90% of CTLA-4 proteins are intracellular and closely positioned to the Golgi apparatus (Valk et al., 2006; Walker
& Sansom, 2015). Surface expression is determined by the strength of the TCR signal.
After TCR binding, CTLA-4 is released to the plasma membrane and rapidly re- internalized and targeted to lysosomal compartments where it is degraded without further stimulus. The half-life of CTLA-4 is around 2h in activated T cells (Valk et al., 2008).
Figure 4. CD28 and CTLA-4 ligands. CD28 and CTLA-4 share same ligands but CTLA- 4 is more likely to bind them. Affinities are represented with the thickness of arrows (Walker & Sansom, 2015).
While CTLA-4 acts early for tolerance induction by regulating the ability of CD28 to bind CD80 or CD86, PD-1 acts late for long-term tolerance maintenance and inhibits CD28 signaling. This inhibition reduces T-cell responses and protect the body against the
26 development of auto proliferative or autoimmune disease (Rudd et al., 2009; Walker, 2017). PD-1 is a cell surface molecule expressed on activated T and B cells. Its ligands are programmed death ligand-1 (PD-L1) and PD-L2 and they are expressed in different kind of cells (Freeman et al., 2000).
2.7 Responses of activation
Primary T cells naturally produce little or no cytokines unless stimulated. Cytokine production is usually assessed after stimulation and cytokine profiles can be used to characterize the activation state of the cells stimulated through specific stimulation method. Cytokine profiles and levels of production of TF are specific of each type of stimulation method, for example, 6 h of stimulation of 106/mL human Peripheral Blood Mononuclear Cells (PBMCs) with 5 ng/mL of Phorbol 12-myristate 13-acetate (PMA) and 1 µg/mL of Ionomycin (Io) results in a higher production of Tumor Necrosis Factor alpha (TNF-α) and gamma interferon (IFN-γ) compared to stimulation with 2.5 µg/mL of Polyhydroxyalkanoates (Baran et al., 2001) In addition, 48 h of incubation with PHA induces production of Tumor Necrosis Factor beta (TNF-ß) and IL-10, which was not induced with PMA/Io (Baran et al., 2001). Other concentrations of PMA/Io were tested and compared with anti-CD3/anti-CD28 stimulation. 24 h incubation with 50ng/mL of PMA and 2 μM/mL of Io induces a higher production of IFN-γ and also IL-17, and significantly less IL-10 compared to anti-CD3/anti-CD28 stimulating antibodies attached to beads (1bead/cell) (Olsen & Sollid, 2013).
During activation, T cells modify their pattern of expression of cell surface glycoproteins.
Therefore, besides looking for proliferation or cytokine production, an additional technique to measure T lymphocyte activation is to look at the relative expression of various relevant surface markers. CD69, for instance, is an Activation Induced Molecule (AIM) and is a reference for early activation of T lymphocytes. CD69 expression on human Peripheral Blood Lymphocytes is detected starting at 3 h post incubation with activators of PKC,
27 such as Mezerein or PMA (Cebrián et al., 1989). CD69 is usually measured in combination with other activation markers that require longer incubation time, such as CD25, which is the α chain of the IL-2 receptor. The peak of expression of human PBL CD25 has been reported at 48h of incubation with 1.14ug/mL of Phytohemagglutinin (PHA) (Poulton et al., 1988).
3. Importance and application of studying activation-proliferation in vitro
Antigen-specific lymphocytes increase their proliferation so more available effector cells will be ready to protect the body during an immune response. Therefore, activation of T cells leads to cell proliferation and this variable can be measured to assess the activation state of the culture. In vitro studies of T cell activation have evidenced molecules with future therapies target potential, for example, checkpoint inhibitors CTLA-4 and PD-1.
Checkpoint-blocking antibodies are trending in cancer immunotherapy, for example ipilimumab, which is an FDA approved agent that blocks CTLA-4 (Hodi et al., 2010). The importance of checkpoint inhibitors in the development of novel treatments was exemplified in 2018, when the Nobel Prize in Physiology or Medicine was awarded to a therapy that combines the blockade of CTLA-4 and PD-1 (The Nobel Prize in Physiology or Medicine 2018, n.d.)
In vitro studies of T cell activation have led to new methods for in vitro T cell stimulation, including antibodies, lectins and phorbols. This allows to pursue in vitro studies including more complex processes such as gene delivery, which efficiency is significantly increased if cells are previously activated (Costello et al., 2000; Zhang et al., 2018). In turn, improvement in these processes is valuable in the manufacturing of ex vivo engineered cell therapies, where gene editing is a major focus, as the CAR T cell therapies. Also, in this same field, the understanding of activation stimuli and signaling that allows an increased proliferation of cells might allow to optimize cell therapies manufacturing time.
28 3.1 In vitro antigen-independent activation methods
3.1.1 Antibodies
In vitro activation of T cells can be mediated by antibodies directed to α and ß chain of the TCR or with anti-CD3 antibodies. Even though TCR is assembled with ζζ CD3 chains, containing 6 ITAMS in total, and CD3 domains ε, γ and δ summarized 4 ITAMS in total (Figure 3) (Kane et al., 2000; Meuer et al., 1983), it has been demonstrated that there are no significant differences about changes in plasma membrane potentials, cell size, increase of intracellular free Ca2+, activation of PKC, IL-2 production, CD25 antigen expression, and DNA synthesis when comparing signaling through TCR or CD3 (Gupta et al., 1991). This antigen-independent activation method induce the cell to achieve higher proliferation rates in cultures of human purified CD4 T cells stimulated with surface- mobilized anti-CD3 in combination with anti-CD28 (Geppert & Lipsky, 1988). Also, anti- CD3 and anti-CD28 antibodies can be covalently coupled with beads similar in size (4.5 M in diameter) to APCs. Both methods, anti CD3/CD28 beads and soluble anti-CD3 with the addition of mononuclear cells as a source of Fc receptor, promote extensive expansion of human purified CD4 and CD8 T cells. After 21 days of activation, beads stimulate larger CD4 T cell expansion (56 fold vs. 27 fold achieved with soluble anti CD3) and both methods stimulate CD8 T cells at the same level (189 fold beads and 186 fold anti-CD3) (Li & Kurlander, 2010). The aim to Culture T cells with anti-CD3 in presence of MNC bearing Fc receptor is to mimic as much as possible physiological antigen presentation and this practice is also known as Rapid Expansion Protocol (Clement et al., 1985).
Table 2. A non-exhaustive list of various published protocols used for stimulation of human cells with antiCD3/anti CD28 beads, and their consequence on cell phenotype as measured in the laboratory
29
30
31 3.1.2 Lectins
The lectin PHA can also stimulate T cells through TCR. PHA is extracted from the red kidney bean (Phaseolus Vulgaris) and binds nonspecifically to the sugars on glycosylated surface proteins, including TCR. More specific, PHA-L subunit binds to the α, β, and γ chains of the TCR (Licastro et al., 1993) and PHE-E binds to erythrocyte membrane compounds (Leavitt et al., 1977; Powell, 1980).
PHA stimulation effect is reported to be dose dependent for CD25 and CD71 (Martín- Romero et al., 2000) and seems that this trend is followed by primary cells and cell lines.
Stimulation of Human PBMCs monocytes depleted with 2mg/mL pf PHA for 48 h results in a 39.2% population CD25+, while stimulation of Jurkat cells in a dose of 5ug/mL for 24h results in a 33% of positive population for CD25 (Shatrova et al., 2015).
Concavalin A (Con A), another plant lectin purified from jack beans (Canavalia ensiformis), also triggers a pro‐inflammatory response in an antigen-independent way (Ando et al., 2014; Stadecker & Leskowitz, 1974; Williams & Benacerraf, 1972) and it is used to induce T cell activation, recruit lymphocytes and elicit cytokine production (Bloksma et al., 1983; Dupuis & Bastin, 1988; Gullberg & Larsson, 1983). It binds to a mannose moiety in the TCR and the rest of the membrane glycoproteins (Ando et al., 2014; Weiss & Stobo, 1984). Con A provides to the cells the first stimulation signal but cells still need the second signal to achieve a full activation state, which could be provided by leptins or CD28. For example, Con A alone, in a dose of 4mg/mL induces 19.9% of CD3+CD4+CD25+ population in human PBCs monocytes depleted but, this positive population increases almost 10% (up to 29.8%) if leptin is added to the culture as a costimulator (Martín-Romero et al., 2000).
3.1.3 PMA and Ionomycin
Induction of T cell activation without binding of any receptor is achieved with PMA and Io.
PMA is a small molecule that mimics DAG in the activation of PKC. Io is a calcium
32 ionophore that enhances Ca2+ influx and as PMA, induces the activation of PKC (Chatila et al., 1989; Cohen et al., 2006; Lomora et al., 2015; Wang et al., 1999).
An example of the diversity of protocols reported to stimulate the cells with these reagents could be seen on table 3. To choose the appropriate stimulation method the population of interest and target molecules of the study must be defined. An example of different behaviors of T cells subsets is a sample of human PBMCs stimulated with 100ng/mL of PMA and 1µM/mL of Io, were CD4+ T cells resulted to be statistically significant more higher producers of TNF-α than CD8+ T cells and both T cell subsets secreted similar amounts of IFN- g (Antas et al., 2004).
Strength of the signal is another variable to take into account. In human CD4+ T cells has been reported that it could influence the cytokine profile. Stimulation of these cells with 100ng/mL of PMA and 4µ/mL of Io for 6h results in a pro-inflammatory profile, characterized by a majority of IL-17 and IFN-γ producing cells. Lower concentrations (10 ng/mL of PMA and 0.4 µ/mL of Io) resulted in a higher production of IL-10 and less IL-17 and IFN-γ (Olsen & Sollid, 2013).
Table 3. A non-exhaustive list of various published protocols used for stimulation of human cells with PMA and Ionomycin, and their consequence on cell phenotype as measured in the laboratory
33
34
4. Continuous cell lines as models of primary cells
For research, working with continuous, also referred to as immortal, cell lines instead of primary cells is common practice due to the many advantages they offer, such as 1- an unlimited supply of a homogeneous population, providing a consistent sample for robust experimentation, 2-the increased reproducibility of results vs. primary samples, and 3- bypassing ethical concerns associated with the use of animal and human tissue (Kaur &
Dufour, 2012). In immunology, one of the references by excellence for T cells are the Jurkat T cells. Jurkats were established from an acute T cell leukemia and have greatly contributed to the characterization of the TCR signaling pathway (Abraham & Weiss, 2004).
However, due to genetic variations in cell lines compared to primary cells, their responsiveness to stimuli might be altered and might not adequately represent primary cells. Cell lines could be a good replacement for primary cells if they display and maintain functional features of primary cells (Kaur & Dufour, 2012).
5. Hypothesis and Objectives
5.1 Hypothesis
Applying in vitro the reported antigen-independent stimulation protocols for human T cells, including as high and low combinations of PMA/Io, or anti-CD3/anti-CD28 Dynabeads™, causes phenotypic changes associated to cell activation such as upregulation of CD69 and CD25 at the cell surface, and an increased proliferation of cells.
5.2 General Objective
35 To evaluate reported antigen-independent stimulation protocols with Dynabeads™
and PMA/Ionomycin in human primary T cells and in human T cell lines in terms of cell proliferation, immunophenotype and gene transcription changes.
5.3 Specific Objectives
1. To evaluate antigen-independent proliferation protocols with Dynabeads™ and PMA/Ionomycin to increase primary human T cells and T cell lines proliferation in vitro.
2. To confirm activation of stimulated primary human T cells and human T cell lines by kinetics analysis of surface expression of CD69 and CD25 with flow cytometry and IL- 2 and CTLA-4 gene transcription with RT-PCR
3. To describe population distribution within cell cycle phases of primary human T cells and Jurkat cell line caused by PMA/Ionomycin stimulation
6. Methodology
6.1 Cell Culture
Jurkat clone E6-1 (cat. TIC-152) and SUP T1 (cat. CRL-1942) cell lines were bought from ATCC. Cells were cultured in RPMI (Gibco, cat. A1049101), supplemented with 10%
inactivated FBS (Gibco, cat. 10438026) and 1% Penicillin/Streptomycin (Gibco, cat.
15140-122) in a confluence between 2 x105 cells/mL up to a maximum of 1 x106 cells/mL for Jurkat and 2 x106 cells/mL for SUP T1. Incubation conditions were 37C and 5% CO2.
6.2 PBMCs Isolation and T cell enrichment
PBMCs were isolated from healthy donor peripheral blood by gradient centrifugation with Ficoll (GE Healthcare cat. 17-1440-02). Blood were transferred into 50 mL centrifuge
36 tubes and diluted 1:1 with PBS (Gibco cat. 10010049) with 2 mM EDTA (Sigma cat.607- 429-00-8). For a 20 mL of blood sample, 2 falcon tubes were used and 10mL of Ficoll were added at the bottom of each one. Samples were centrifuged in a swing centrifuge at 450 g for 30 min at 18°C, with an acceleration of 4 and a brake deceleration of 0.
Plasma supernatant was removed carefully with a pipette. Buffy coat at the interface was transferred into a clean 50 ml falcon tube with 1 mL tip. Tube was filled up to 45 mL with PBS-EDTA and centrifuged at 600 g for 7 min. Pellet was resuspended in RPMI 10%
FBS and viable cells were counted in a Neubauer chamber with trypan blue.
For pan-T cell isolation used Miltenyi kit cat. 130-096-535. First, for each 107 PBMCs in the pellet, 40 µL of MACS Buffer (PBS, 2 mM EDTA, 0.5% FBS) were pipetted to resuspend it. Suspension was then incubated 5 min with 10 µL of Pan T cell Biotin- Antibody cocktail. Time passed, added 20 µL of Pan T cells Microbead cocktail and incubated 10 min. Incubations were at 4°C, in the dark. For cell separation, Miltenyi MultiStand, Miltenyi MiniMACS separator (cat. 130-042-401)(stored at -20C) and Miltenyi MS columns (cat. 130-042-201) were used to separate a maximum of 107 magnetically labeled cells in 106-2x108 total PBMCs. Before starting, a pre-separation filter (Miltenyi cat. 130-041-407) was adapted at the top of the column. Each column was activated by passing 500µL of degassed MACS Buffer and immediately after it, the sample was passed through the column. Once T cells were collected, they were counted and plated.
6.3 Stimulation plating
Different stimulation protocols were tested. For the first set of stimulation protocols, to count the cells at days 2, 4 and 6, worked with primary enriched T cells, PBMCs, Jurkat cells and SUP T1 cells. Primary cells were plated at a concentration of 5x105 cells/mL while cell lines were plated at 2x105 cells/mL. Cells were plated in wells of a 96 well plate with a final volume of 200 µL. Everything was plated in triplicates.
Amount of cells for each treatment was put into an Eppendorf tube, including the extra 10%. For example, for 3 wells of Jurkat the amount of cells needed including the extra
37 10% are 1.1x105 cells.These cells were pipette into an Eppendorf tube, centrifuged at 200 g for 5 min and resuspend in a previously prepared medium containing already the stimuli. Cells were then plated and once all the experiment was plated, checked at the microscope all the wells and plate was incubated.
Activation mediums were prepared at 1X. For negative control, nothing was added to the regular culture medium. For 1 mL of medium of PMA/Io in low concentrations (10 ng/mL and 1ug/mL, accordingly), used 1 µL of PMA at 10 ng/mL (Sigma cat. P8134-1116 lot.
MKCG5702) and 1 µL of Io at 1 ug/mL (Sigma 10634-1 lot. 02944039v). For 1 mL of medium of PMA/Io in high concentrations (200 ng/mL and 2 ug/mL, accordingly), used 20 µL of stock PMA and 2 µL of stock Io.
For anti-CD3/anti-CD28 Dynabeads™ activation, manufacturer’s indications were followed. Briefly, each well should contain 8 x104 cells in a 1:1 ratio with beads, equivalent to 2 µL of beads (Gibco cat. 11131D lot. 834559) and 30 U/mL of rIL-2, equivalent to 2 µL of IL-2 at 3 UI/mL (Gibco PHC0021 lot.2071748). Before being added to the medium, Dynabeads™ were pipetted into a microcentrifuge tube with 1mL of PBS and vortexed for 3 seconds. Tube was then put into the magnet MagnaRak (Invitrogen cat. CS15000) for 2 min until the Dynabeads™ could be seen at the border of the tube, attracted by the magnet. Without lifting the tube from the MagnaRak, PBS was removed. Tube could be then be separated from the magnet to resuspend the beads in the medium and added the medium and IL-2 needed.
For the second round of stimulation methodologies worked with PBMCs in a concentration of 106cells/mL and Jurkat cells in a concentration of 2x105 cells/mL. Cell count was performed with PBMCs only. For this, plated in triplicates each treatment, used wells of a 96 well plate and total medium of 100µL. For Flow cytometry, plated in wells of a 24 well plate with a total volume of 1 mL. Activation mediums were supplemented with 100 UI/mL of rIL-2 or 100 UI/mL of rIL-2 plus Dynabeads™ (in a 1:1 cell ratio).
For CTLA-4 flow cytometry, PBMCs and Jurkat cells were stimulated with 50 ng/mL of PMA and 1 µg/ml of Io. Cells were plated at 5x105 cells/mL in wells of a 24 well plate and
38 incubated for 24 h. Finally, for gene transcription cells were stimulated with 100 ng/mL of PMA and 1 µg/ml of Io during 6 h.
6.4 Cell count analysis
Cells were stained with trypan blue and counted in a Neubauer chamber. For each treatment and cell type, cells/mL were calculated and plotted in Excel. For the treatments in which a greater number of cells was counted than the control, a statistical analysis was performed in Minitab to corroborate if the increase was significant. The normality of the data was determined with an Anderson-Darling test and then, comparison of means was performed with T-Student, an Analysis of Variance (ANOVA) and a post-hoc Tuckey test or a Mann-Whitney test, accordingly. All results were reported with a 95% of confidence.
6.5 Flow Cytometry 6.5.1 Staining
Cell staining were done following the specific antibodies’ manufacturer’s protocol. For each sample, 5 x105 cells in a total volume of 50µL were prepared (including antibody- fluorochrome volume). Cells were pipetted into a microcentrifuge tube, pelleted at 200 g for 5min and washed twice with 1 mL of PBS. After this, we continued with the staining protocol according to the experiment.
To study the activation immunophenotype, pellets were resuspended in 42.7 µL of prepared Fixable Viability Stain 620 (BD cat. 564996 lot.031480 ) and 2.5 µL of APC- R700-anti-CD3 (BD cat. 565119 lot.86216 ), 2.5 µL of APC-H7-anti-CD25 (BD cat.
560225 lot.9118) and 2.5 µL of PerCP Cy5.5-anti-CD69 (BD cat. 560738 lot.286762) were added. Samples were then incubated 30 min in dark at 4°C. Time passed, washed
39 twice with 1 mL of PBS, spinning at 200 g for 5 min. Finally, each pellet was resuspended in 200 µL and kept on ice, covered from light, until read. This staining required compensation. Autofluorescence population control was a tube with unstained cells. FVS 620 control was a tube stained with half of the population alive and the other heat killed by incubation of for 5 min at 60°C. Controls for anti-CD3, anti-CD69 and anti-CD25 were compensation beads (BD cat.552843) stained independently with one fluorochrome each.
For ell cycle analysis samples were stained first with 2.5 µL of APC-R700-anti-CD3 and then, fixed and permeabilized prior to stain with Ki-67 and 7-AAD. For this, Cytofix Cytoperm kit was used according to manufacturer’s protocol (BD cat.554714 lot.7346888). Briefly, once samples were stained with anti-CD3, pellets were resuspended in 125 µL of fix/perm solution and incubated 20 min in dark at 4°C. Time passed, samples were washed twice with 500 µL of Perm/Wash solution, spinning at 250 g for 5 min. Then, pellets were resuspended in 25 µL of Per/Wash and added 10 µL of FITC-anti-Ki-67 (BD cat.556016 lot.8043921) and or 100 µL of 7-AAD (BD cat.559925 lot.7086885). Samples were incubated 20 min in dark at 4°C. Time passed, washed samples twice with 1 mL PBS and resuspended in 150 µL PBS and read. This staining also required compensation. Autofluorescence population control was a tube with unstained cells. 7-AAD control was a tube stained with half of the population alive and the other heat killed and Ki-67 control were beads stained with a FITC fluorochrome.
To measure apoptosis, samples were stained with the Annexin V (AnnV) Apoptosis Detection kit (BD. Cat.556547 lot.4072590). For this, cells were washed with 500 µL of cold PBS and resuspended in 50 µL of cold AnnV Binding Buffer. To stain, 2.5 µL of FITC- AnnV and 2.5 µL of 7-AAD were added and incubated 15 min at room temperature, covered from light. Time passed, added 200µL of Binding Buffer and read at cytometer within 1 h.
Finally, for CTLA-4 staining, BV421-anti-CTLA-4 (BD cat. 562743 lot. 8255969) was used.
From each sample 2 separate tubes were prepared, one to stain extracellular CTLA-4
40 and the other to stain intracellular CTLA-4. First, extracellular CTLA-4 were stained by resuspended the pellet in 47.5 µL of PBS and added 2.5 µL of fluorochrome. Sample were incubated 30 min in dark at 4°C. Time passed, washed twice with 1 mL of PBS.
Then, all the samples (for intra and extracellular staining and unstained sample) were fixed with CytoFix Cytoperm kit. For this, samples were pellet and resuspend in 125 µL of fix/perm solution and incubated 20 min in dark at 4°C. After this, washed twice with 500 µL of Perm/Wash solution, spinning at 250 g for 5 min. Then, unstained sample and the one for extracellular staining were resuspend in 200 µL of PBS and stored in dark at 4°C until read. Meanwhile, intracellular staining sample was resuspended in 47.5 µL of Perm/Wash solution and 2.5 µL of fluorochrome and was incubated 20min in dark at 4°C.
Time passed, washed twice with 500 µL of Perm/Wash solution and resuspend in 200 µL of PBS and read all samples at cytometer.
.
6.5.2 Gating and analysis
All the samples were read with the cytometer BD FACS Celesta, with a 3 lasers (red, blue and violet) configuration that allows to work with panels of up to 12 colors. A minimum of 104 events were recorded for each sample with the software BD FACS Diva. Subsequent analyzes were done with FlowJo software v.10.7.2. When necessary, compensation was achieved first and then, analysis of all properly compensated samples were done.
To analyze the expression of CD69 and CD25 the population was first checked in the SSC-A/FSC-A dot plot. Then, its visualization was changed to an FSC-H/SFC-A dot plot and gated for single cell events (singlets) (area and high are proportional so the population should have a distribution of a line with an inclination of 45°). Selected singlets were visualized in a viability/CD3 (PI-A/APC-R700-A) dot plot divided in quadrants placed to delimit the fluorescence emissions of unstained samples so, events outside of the quadrants were considered positive for the respective fluorochrome. The population negative for viability dye and positive for CD3 was selected and visualized in a dot plot
41 CD69/CD25 (PerCP-Cy5.5-A/APC-H7-A) divided in quadrants placed on unstained samples (Figure 5). From each sample, we obtained the percentage of positive population for each fluorochrome and the Median Fluorescence Intensity (MFI) of the population.
Figure 5. Representative ancestry gating for CD69 and CD25 analysis on T cells. FSC/
SSC of a representative population (A); Singlets selection from A (B); Quadrant position based on Viability control (dead and alive cells in the same sample; Y axis) and CD3 negative sample (X axis) from B (C). Visualization of the viable (PI-) and CD3+ population from A (D); Expression of CD69 (PerCP-Cy5.5. Y axis) and CD25 (APC-R700. X axis) from D (E).
For each fluorochrome, stimulation Index (SI) was calculated by dividing the MFI of the stimulated sample by the MFI of the control sample (without stimulus). Population distribution according to the surface expression of CD69 and CD25 were summarized in a table and SI for each surface marker were graphed.
To complement to the expression of surface markers, the distribution of cells within the cell cycle was measured too by flow cytometry, before and after stimulation with high PMA/Io in PBMC and Jurkat cells. 7-AAD and Ki-67 staining was done as detailed on section 6.5.1. Population analysis and gating was first done by visualizing the population spread SSC-A/FSC-A (Figure 6, panel A). Then, changed visualization to FSC-H/SFC-A and gated for single cell events (singlets) (area and high are proportional so the
42 population should have a distribution of a line with an inclination of 45°) (Figure 6, panel B). Selected singlets were visualized in an histogram with CD3 on the X axis (APC-R700- A). CD3+ gate was previously stablished based on CD3- population. (Figure 6, panel C).
The distribution of the population at each stage of the cell cycle was determined with Dean-Jett-Fox model, available in FlowJo (Figure 6, panel D). For cases in which the model does not fit the population, population was then displayed in a Ki-67-A/7-AAD dot plot and gated for each cell cycle phase (Figure 6, panel E). G1 population was first gated and defined its position on the X axis as the DNA Index with a value of 1. Then, gate the G2 population located with a DNA index of 2 (Note that this gate is wider than that of G1, it extends to the right since it was adjusted based on the prediction of the model (Figure 6, panel D)). In between G1 and G2 gated population in S phase. Population in both, G2 and M phase could be localized at the same DNA index and are differentiate with the Ki- 67 expression, for which M-phased cells are positives.
43 Figure 6. Representative ancestry gating for cell cycle with Ki-76 and 7-AAD. FSC/ SSC of a representative T cell population (A); Singlets selection from A (B); CD3+ selection population from B (C). Distribution of population from C on each cell cycle phase according to Dean-Jett-Fox model (D). Distribution of population from C on each cell cycle phase according to DNA Index.
Parallel to cell cycle analysis, a sample from same population was stained for apoptosis detection with AnnV and 7-AAD. To analyze the data, population was first checked in the SSC-A/FSC-A dot plot. Then, its visualization was changed to an FSC-H/SFC-A dot plot and gated for single cell events (singlets) (area and high are proportional so the population should have a distribution of a line with an inclination of 45°). Selected singlets were visualized in a
Figure 7. Representative ancestry gating for apoptosis detection. SSC-A/FSC-A of a representative T cell population (A); Singlets selection from A (B); CD3+ selection population from B (C). Distribution of population from C on according to its membrane permeability (7-AAD-A and is phosphatidylserine exposure (FITC-A) (D).
Finally, expression analysis of intra and extracellular CTLA-4 was performed by calculating the SI of the intra and extracellular CTLA-4. First, population was visualized in a FSC-H/FSC-A dot plot and singlets cells were gated. Then selected the CD3+ population from singlets based on unstained sample (Figure 8). SI of these CD3+ cells
44 was calculated by dividing the MFI of the stimulated sample by the MFI of the stimulated sample. One SI was calculated for each CTLA-4 location (intracellular and extracellular).
Obtained SI were graphed and compared.
Figure 8. Representative ancestry gating for CTLA-4 expression analysis a representative T cell population. Singlets selection(A); CD3+ selection population from A (B).
6.6 Gene transcription (RT-PCR)
Gene transcription of IL-2 and CTLA-4 was analyzed using end-point RT-PCR. For this, 2 x106 cells were centrifuged at 200 g for 5 min. Pellet was resuspended in 250 µL of PBS and added 750 µL of TRIzol™ (Ambion cat.15596026). Sample was homogenized and incubated for 5 min at room temperature. Then, added 0.2 mL of chloroform and mixed until TRIzol™ looked turbid. Incubated again 3 min and centrifuged for 15 min at 12 000 g at 4°C. After that, the aqueous phase was transferred to a new nuclease-free microcentrifuge tube by angling the tube at 45° and pipetting the solution out.
To precipitate RNA, 0.5 mL of isopropanol were added to the aqueous phase, incubated at room temperature and centrifuged for 10 min at 12 000 g at 4°C. Supernatant was discarded with a micropipettor and pellet was resuspended in 1 mL of 75% ethanol. After this, sample was vortexed briefly, and centrifuged for 5 min at 7 500 g at 4°C. Supernatant was discarded with a micropipettor and pellet was air dried for 5–10 min. After this, pellet
45 was resuspended in 20–50 µL of RNase-free water. RNA quality and concentration was measured at the nanodrop.
For gDNA digestion and cDNA synthesis used RT Superscript IV VILO MM with Dnase (ThermoFisher cat.11766050). Two qPCR tubes (Corning cat.3745) were prepared with the gDNA digestion reaction mix: 1 µL of 10X ezDNase Buffer, 1 µL of ezDNase enzyme, 2.5 µg of template RNA and completed volume up to 10 µL with nuclease free water.
Samples were incubated 2 min at 37°C and then, added components to prepare the RT and no RT Control reaction mixes: 6 µL of nuclease free water and 4 µL of SuperScriptTM IL VILOTM no RT control or 4 µL of SuperScriptTM IL VILOTM Master Mix. Solutions were gently mixed and incubated at 25°C for 10 min to anneal primers. Time passed, increased temperature at 50°C for 10 min to reverse transcribe RNA and then, increased again up to 85°C for 5 min to inactivate enzyme.
Finally, a tube for each set of primers and condition was prepared for the PCR. Each reaction tube contained 12.5 µL of GoTaq Green master Mix (Promega cat.M7122), 0,04 µL of each primer at 10 nM stock (forward and reverse) and 12.42 µL of nucleases free water with 5-10 ng of cDNA. Primers: CTLA-4 forward: 5- CTCTACATCTGCAAGGTGGAG-3; CTLA-4 reverse: 5-CCCTGTTGTAAGAGGGCTTC- 3 ; IL-2 forward: 5-AAGTTTTACATGCCCAAGAAGG-3 ; IL-2 reverse: 5-AAG
TGAAAGTTTTTGCTTTGA GCTA-3; ß-actin forward: 5-
CATGGGTCAGAAGGATTCCTATGTG-3 ; ß-actin reverse: 5-ATAGCA CAGCCTGGATAGCAACGTA-3. Thermocycle was set as 2 min at 50°C, followed by 2 min at 95°C, there were 30 cycles of 15 s 95°C, 15 s at annealing temperature and 1min at 62°C. Annealing temperature were different for each set of primers, for CTLA-4 and ß- actin was set in 58°C, and for IL-2 in 54°C.
Samples were then run in an 1% agarose gel for 50min at 60V. Thirty mL gel were prepared by dissolving 0.3 g of agarose (Promega cat.V3121 lot.85707) in 30 mL of TAE buffer and 3 µL of SYBR safe DNA gel stain (Invitrogen cat.P/N-S33102 lot.2009284) were added. While the gel solidified, 5 ng and 10 ng of each sample in a total volume of 10 µL was prepared by mixing it with 3 µL of gel loading die (New England Biolabs
46 cat.B7024S lot.10065747). Molecular weight marker 1 Kb DNA ladder (Promega cat.G571A lot.270649) was prepared by 1µL of solution mixed with 3 µL of dye/loading buffer.
7. Results
7.1 Specific Obj. 1: To investigate antigen-independent proliferation protocols previously described to increase human T cells proliferation in vitro
The first tested protocol of stimulation with PMA/Io consisted of the combination of concentrations of PMA and Io previously reported (Table 1), such that one would have relatively low concentrations of both (10 ng/mL PMA and 1 µg/mL Io) (referred as low PMA/Io) and the other would have high concentrations of both (200 ng/mL PMA and 2 µg/mL Io) (referred as high PMA/Io). In parallel, a protocol of stimulation with anti- CD3/anti-CD28 coated microbeads was also trialed (Dynabeads™), following manufacturers’ proposed protocol.
Concentrations of PBMCs calculated from manual counts in a Neubauer chamber showed that unstimulated cells had a significantly higher cell density for each day counted, compared to both PMA/Io protocols tested and higher concentration of PMA/Io leaded to the lowest counts (Figure 9, panel A), cell concentrations/mL for day 2, 4 and 6, for unstimulated cultures were 332000±31241, 256000±34641, 344000±44542, respectively; for low PMA/Io stimulated cultures were 216000±13856, 160667±37112, 183000±21517 respectively; and for high PMA/Io stimulated cultures were 210667±18903, 150667±12220, 134667±26026 respectively). Day 2 always had the highest concentration of cells, followed by a significant drop on day 4. On day 6, untreated cells had a cell density similar to what was observed at day 1, while PMA/Io treated cells had a lower density on day 6 than on day 4. However, decreases were not significant (Figure 9, panel A). Stated statistically significant differences were determined by one- way ANOVA with an α of 0.05. Obtained P-value was < 0.001, therefore, a post-hoc Tucket test was performed.
