Maintained thymic output of conventional and
regulatory T cells during human pregnancy
Sandra Hellberg, Ratnesh Bhai Mehta, Anna Forsberg, Göran Berg, Jan Brynhildsen,
Ola Winqvist, Maria Jenmalm and Jan Ernerudh
The self-archived postprint version of this journal article is available at Linköping
University Institutional Repository (DiVA):
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-154564
N.B.: When citing this work, cite the original publication.
Hellberg, S., Bhai Mehta, R., Forsberg, A., Berg, G., Brynhildsen, J., Winqvist, O., Jenmalm, M., Ernerudh, J., (2019), Maintained thymic output of conventional and regulatory T cells during human pregnancy, Journal of Allergy and Clinical Immunology, 143(2), 771-775.e7.
https://doi.org/10.1016/j.jaci.2018.09.023
Original publication available at:
https://doi.org/10.1016/j.jaci.2018.09.023
Copyright: Elsevier
Letter to the editor 1
Manuscript number: JACI-D-17-01584 2
3
Maintained thymic output of conventional and regulatory T cells during human pregnancy 4
5
Sandra Hellberg, MSc1*, Ratnesh B. Mehta, PhD1, Anna Forsberg, PhD1, Göran Berg, MD, PhD2, Jan 6
Brynhildsen, MD, PhD2, Ola Winqvist, MD, PhD3, Maria C. Jenmalm, PhD1, Jan Ernerudh, MD, PhD4 7
8
1Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and Immune Regulation, 9
Department of Clinical and Experimental Medicine, Linköping University, 581 85 Linköping, Sweden 10
2Division of Obstetrics and Gynecology, Department of Clinical and Experimental Medicine, Linköping 11
University, 581 85 Linköping, Sweden 12
3Unit of Translational Immunology, Department of Medicine, Karolinska Institute, 171 76 Stockholm, 13
Sweden 14
4Department of Clinical Immunology and Transfusion Medicine and Department of Clinical and 15
Experimental Medicine, Linköping University, 581 85 Linköping, Sweden 16
17
*Correspondence address: Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and 18
Immune Regulation, Department of Clinical and Experimental Medicine, Pathology Building Level 10, 19
SE 581 85, Linköping, Sweden. Tel: +46 10 10 37357; Fax: +46 13 132257; Email address: 20
sandra.hellberg@liu.se 21
22
Declaration of funding: This study was funded by the Swedish Research Council (grant number 23
K2013-61X-22310-01-4) and the Medical Research Council of Southeast Sweden (grant number 24
FORSS-573421). 25
Capsule summary: In contrast to the rodent-based conception, the output of CD4+ T-cells is 27
preserved, and for Treg cells even increased, during human pregnancy. This indicates a central 28
thymic role in tolerance needed for a successful pregnancy. 29
30
Keywords: CD4+ T cells; Human pregnancy; Recent thymic emigrants; Thymus; TREC 31
32
Abbreviations used: RTE, recent thymic emigrant; Tconv cell, conventional T cell; Th-cell, T helper 33
cell; TREC, T cell receptor excision circle; Treg, regulatory T cell 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55
To the Editor: 56
57
During pregnancy, immunological tolerance towards the semi-allogeneic fetus needs to be 58
established whilst at the same time an effective immune defense must be maintained1. The 59
pregnancy-associated thymic involution reported in rodents2 has been suggested to support 60
maternal immune regulation by reducing the output of potentially harmful T helper (Th) cells. 61
However, the functional importance of this thymic involution remains unclear and it is not known if it 62
even occurs in humans3. In fact, the role of thymus during human pregnancy and in pregnancy-63
associated tolerance remains largely unknown4, albeit a role for thymic-derived T regulatory (Treg) 64
cells in pregnancy complications has been suggested4, supporting a role for thymus in immune 65
regulation during human pregnancy. The aim of this study was to assess the role of thymus in Th-cell 66
regulation during human pregnancy by analyzing the output of different Th-cell populations. 67
68
To determine if pregnancy influences thymic function we used RT-PCR to analyze T cell receptor 69
excision circle (TREC) content in flow cytometry sorted Th-cell subpopulations (Fig 1, A-B) in 2nd 70
trimester pregnant and non-pregnant women (see detailed methods and Table E1 in this article’s 71
Online Repository at www.jacionline.org). TREC content is a well-established measure of cells with 72
recent thymic origin5, based on the presence of episomal DNA fragments, generated during the T cell 73
receptor rearrangement in the thymus, and since TRECs are not duplicated during mitosis they are 74
diluted with each cell division. Consequently, cells with a more recent thymic origin will have a higher 75
TREC content compared with Th-cells that have undergone peripheral post-thymic proliferation5. As 76
expected, TREC content was significantly higher in cells with a naive (CD45RA+) phenotype, 77
compared with memory (CD45RA-) cells (p=<0.0001; Fig 1, C), hence validating our PCR assay to 78
measure TREC. We found that 2nd trimester pregnant, compared with non-pregnant, women had 79
significantly higher TREC levels (p=0.043: Fig 1, D) in the naive Treg population (defined as 80
CD25++CD45RA+Foxp3+), indicating an increased thymic output of Treg cells in pregnancy. The TREC 81
content did not differ in the naive T conventional (Tconv; CD25-CD45RA+) cells (Fig 1, E), in line with a 82
maintained output of conventional Th-cells in pregnancy. 83
84
To corroborate and extend the finding of maintained or increased thymic output during pregnancy, 85
we used CD31 expression, assessed by flow cytometry, as an additional marker of recent thymic 86
emigrants (RTEs)6. Here, we investigated thymic output in both the 2nd and 3rd trimesters of 87
pregnancy, i.e. the period when pregnancy-induced immune modulation is most pronounced (Fig 2, 88
A and see Table E1 and Fig E1 in this article’s Online Repository at www.jacionline.org). CD31+, as 89
opposed to CD31-, naive T cells are significantly enriched for TRECs7, and in agreement, we show that 90
naive T cells, with higher TREC content, also have higher CD31 expression compared with memory T 91
cells (p<0.0001, see Fig E2 in this article’s Online Repository at www.jacionline.org). CD31 and TRECs 92
are known to correlate, although with a slight difference in dynamics8. Overall, we found that 93
pregnant and non-pregnant women had similar proportions and absolute numbers of RTE Tconv 94
(CD31+ Foxp3-CD45RA+) cells (Fig 2, B-C), supporting a maintained output of the majority of T cells 95
during pregnancy. The significantly higher RTE Tconv cell count that was noted in 3rd trimester 96
compared to 2nd trimester pregnant women (p=0.0036, Fig 2, C) most likely reflects the 97
corresponding increase noted in total CD4+ T cell counts in the 3rd trimester (compared to the 2nd 98
trimester, p=0.0067; data not shown). In contrast to the TREC-based difference in Treg cells, we 99
found no differences between non-pregnant and pregnant women, neither in the 2nd nor in the 3rd 100
trimester, concerning the proportion and absolute numbers of RTE Treg cells (CD31+ 101
FoxplowCD45RA+)(Fig 2, D-E). This was also true for the cellular level of expression of CD31 (median 102
fluorescent intensity; data not shown). The reason why CD31 findings did not corroborate the TREC-103
based increase in the Treg population might be the difference in dynamics of these markers. Indeed, 104
CD31 expression is maintained on naive T cells for several rounds of homeostatic proliferation whilst 105
TREC levels decrease8, supporting the notion that differences in kinetics may well explain the 106
difference in our findings regarding Treg cells when based on CD31 (maintained output) or TREC 107
(increased output). 108
109
Proliferation of T cells influences TREC levels, although proliferation in naive T cells is assumed to be 110
too low to significantly affect TREC levels. However, indications of a more activated maternal 111
immune system during pregnancy9 prompted us to make a more detailed analysis of the dynamics of 112
the T cell pool (for gating strategies see Fig E1 in this article’s Online Repository at 113
www.jacionline.org). Overall, we found no indications of increased proliferation in naive and memory 114
Th-cell subsets during pregnancy, neither when comparing pregnant and non-pregnant women, nor 115
when comparing the 2nd and 3rd trimesters of pregnancy (see Fig E3 in this article’s Online Repository 116
at www.jacionline.org). Instead, we found significantly lower Ki67 expression in RTE Tconv cells in 117
pregnant women compared with the non-pregnant state, which could affect measured TREC levels, 118
albeit Ki67 expression was very low in all groups (see Fig E3, B in this article’s Online Repository at 119
www.jacionline.org). Another factor that potentially could affect measured RTE frequencies, and 120
hence also TREC content, is peripheral consumption, leading to a different distribution of 121
subpopulations. However, we found no major shifts in the T cell distributions as pregnant and non-122
pregnant women had similar proportions of mature naive (CD31-CD45RA+) and memory Tconv and 123
Treg cells, as well as of non-suppressive Foxp3+Th cells (see Fig E4 in this article’s Online Repository 124
at www.jacionline.org). Taken together, it is unlikely that peripheral events such as proliferation and 125
consumption of cells have had a large impact on our results. 126
127
In conclusion, we found that thymic output of both Tconv and Treg cells is maintained during 128
2nd and 3rd trimester human pregnancy. The output of Treg cells may even be increased, which would 129
fit with the demand for fetal tolerance during pregnancy and could also contribute to the pregnancy-130
associated improvement of autoimmune diseases, like multiple sclerosis, that are associated with 131
defects in thymic function. Our findings challenge the general conception, based on studies in 132
rodents, of an inactive thymus during pregnancy, but rather support a maintained and important 133
function of thymus in human pregnancy. 134 Sandra Hellberg, MSc 135 Ratnesh B. Mehta, PhD 136 Anna Forsberg, PhD 137 Göran Berg, MD, PhD 138 Jan Brynhildsen, MD, PhD 139 Ola Winqvist, MD, PhD 140 Maria C. Jenmalm, PhD 141 Jan Ernerudh, MD, PhD 142 143
Conflicts of interest: None 144
145
Sandra Hellberg, MSc: Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and 146
Immune Regulation, Department of Clinical and Experimental Medicine, Linköping University, 581 85 147
Linköping, Sweden 148
149
Ratnesh B. Mehta, PhD: Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and 150
Immune Regulation, Department of Clinical and Experimental Medicine, Linköping University, 581 85 151
Linköping, Sweden 152
153
Anna Forsberg, PhD: Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and 154
Immune Regulation, Department of Clinical and Experimental Medicine, Linköping University, 581 85 155
Linköping, Sweden 156
157
Göran Berg, MD, PhD: Division of Obstetrics and Gynecology, Department of Clinical and 158
Experimental Medicine, Linköping University, 581 85 Linköping, Sweden 159
Jan Brynhildsen, MD, PhD: Division of Obstetrics and Gynecology, Department of Clinical and 161
Experimental Medicine, Linköping University, 581 85 Linköping, Sweden 162
163
Ola Winqvist, MD, PhD: Unit of Translational Immunology, Department of Medicine, Karolinska 164
Institute, 171 76 Stockholm, Sweden 165
166
Maria C. Jenmalm, PhD: Division of Neuro and Inflammation Sciences, Unit of Autoimmunity and 167
Immune Regulation, Department of Clinical and Experimental Medicine, Linköping University, 581 85 168
Linköping, Sweden 169
170
Jan Ernerudh, MD, PhD: Department of Clinical Immunology and Transfusion Medicine and 171
Department of Clinical and Experimental Medicine, Linköping University, 581 85 Linköping, Sweden 172
173
Reference list 174
1. Mor G, Aldo P, Alvero AB. The unique immunological and microbial aspects of pregnancy. Nat 175
Rev Immunol 2017; 17:469-82. 176
2. Clarke AG, Kendall MD. The thymus in pregnancy: the interplay of neural, endocrine and 177
immune influences. Immunol Today 1994; 15:545-51. 178
3. Swami S, Tong I, Bilodeau CC, Bourjeily G. Thymic involution in pregnancy: a universal 179
finding? Obstet Med 2012; 5:130-2. 180
4. Wagner MI, Mai C, Schmitt E, Mahnke K, Meuer S, Eckstein V, et al. The role of recent thymic 181
emigrant-regulatory T-cell (RTE-Treg) differentiation during pregnancy. Immunol Cell Biol 182
2015; 93:858-67. 183
5. Kong FK, Chen CL, Six A, Hockett RD, Cooper MD. T cell receptor gene deletion circles identify 184
recent thymic emigrants in the peripheral T cell pool. Proc Natl Acad Sci U S A 1999; 96:1536-185
40. 186
6. Tanaskovic S, Fernandez S, Price P, Lee S, French MA. CD31 (PECAM-1) is a marker of recent 187
thymic emigrants among CD4+ T-cells, but not CD8+ T-cells or gammadelta T-cells, in HIV 188
patients responding to ART. Immunol Cell Biol 2010; 88:321-7. 189
7. Junge S, Kloeckener-Gruissem B, Zufferey R, Keisker A, Salgo B, Fauchere JC, et al. Correlation 190
between recent thymic emigrants and CD31+ (PECAM-1) CD4+ T cells in normal individuals 191
during aging and in lymphopenic children. Eur J Immunol 2007; 37:3270-80. 192
8. Kilpatrick RD, Rickabaugh T, Hultin LE, Hultin P, Hausner MA, Detels R, et al. Homeostasis of 193
the naive CD4+ T cell compartment during aging. J Immunol 2008; 180:1499-507. 194
9. Steinborn A, Rebmann V, Scharf A, Sohn C, Grosse-Wilde H. Soluble HLA-DR levels in the 195
maternal circulation of normal and pathologic pregnancy. Am J Obstet Gynecol 2003; 196
188:473-9. 197
Figure legends 198
Fig 1. TREC levels in pregnant and non-pregnant women. (A) Representative flow cytometry dot plot 199
for sorting strategy. (B) Foxp3 mRNA expression determined by RT-PCR in sorted T cell 200
subpopulations (n=4 non-pregnant, n=4 pregnant). TREC levels in sorted (C) memory Treg and Tconv 201
cells compared to naive T cell subsets, (D) naive Treg cells and (E) naive Tconv cells, determined by 202
RT-PCR using GAPDH as a reference gene. Missing values are due to limited availability in the number 203
of cells required for analysis. Median and interquartile ranges are shown. *P<0.05, ****P<0.0001
.
n, 204naive; m, memory; TREC, T cell receptor excision circles; Tconv, conventional T cell; Treg, regulatory T 205
cell. 206
207
Fig 2. RTE (CD31+CD45RA+) subsets in pregnant and non-pregnant women. (A) Representative flow 208
cytometry dot plots for gating strategies. Proportion and absolute numbers of RTE Tconv cells (B,C) 209
and RTE Treg cells (D,E) analyzed by flow cytometry. Missing values are due to limited availability in 210
the number of cells required for analysis. Mean and standard deviations are shown. **P<0.01. Treg, 211
regulatory T cell; Tconv, T conventional; RTE, recent thymic emigrants. 212
1 Online Repository for:
1
Maintained thymic output of conventional and regulatory T cells during human pregnancy 2
Manuscript number: JACI-D-17-01584 3
4
Authors: 5
S. Hellberg, MSc,a* R.B. Mehta, PhD,a A. Forsberg, PhD,a G. Berg, MD, PhD,b J. Brynhildsen, MD, PhD,b 6
O. Winqvist, MD, PhD,c M.C. Jenmalm, PhD,a J. Ernerudh, MD, PhDd 7
8
Supplementary materials and methods: 9
10
Subjects 11
A total of 56 healthy pregnant women (n=30 second trimester pregnant, n=26 third trimester 12
pregnant) with no signs of pregnancy complications at inclusion, visiting the maternity care unit in 13
Norrköping, Sweden, were included in the study. A review of medical records following delivery, 14
showed that two pregnant women (recruited in the 2nd trimester) had delivered preterm (before 15
gestational week 37) and were therefore not considered as normal pregnancies and were excluded. 16
In addition, one woman (2nd trimester) who received Tinzaparin (Innohep) three days prior to blood 17
sampling was also excluded due to the potential immunological effects of low-molecular weight 18
heparinE1. Of the remaining 27 2nd trimester pregnant women (see Table E1 in this article’s Online 19
Repository at www.jacionline.org), it was decided that the following three women should remain 20
included: one woman who subsequently developed intra-hepatic cholestasis but delivered at term 21
(gestational week 42), hence considered healthy at the time of blood sampling; one woman on anti-22
histamine (Cetirizine) treatment; one woman on selective serotonin reuptake inhibitor (SSRI) and 23
inhalation budesonide (Pulmicort) treatment. Of the 26 included 3rd trimester pregnant women (see 24
table E1 in this article’s Online Repository at www.jacionline.org), it was decided that the following 25
women should remain included: two women on SSRI; two women on Trombyl and three women who 26
2 used of pain medication (Citodon). Thirty non-pregnant women were recruited amongst students 27
and personnel at Linköping University and Linköping University Hospital (see Table E1 in this article’s 28
Online Repository at www.jacionline.org). All non-pregnant women were healthy and had normal 29
blood cell counts. One non-pregnant control reported use of inhalation budesonide (Pulmicort) and 30
terbutaline sulfate (Bricanyl Turboinhaler) treatment and two controls used SSRIs. There were no 31
significant differences between the groups in terms of age, smoking or parity. The pregnant women 32
had been pregnant significantly more times compared to the non-pregnant controls (p=0.012 for 2nd 33
trimester vs. HC and p=0.004 for 3rd trimester vs HC). Due to limitations in cell numbers available 34
from each woman, different numbers of subjects are included in the different analysis. All women 35
gave written informed consent prior to inclusion and blood sampling. The study was approved by the 36
regional ethical review board in Linköping (M39-08). 37
38
Sample preparation 39
Blood was collected in an EDTA-tube (BD Vacutainer®; BD Biosciences, Franklin Lakes, NJ, USA) 40
for flow cytometry and in sodium-heparin tubes (Greiner Bio-One, Kremsmünster, Austria) for 41
isolation of peripheral blood mononuclear cells (PBMCs) for cell sorting and subsequent analysis of T 42
cell receptor excision circle (TREC) content with PCR. PBMCs were isolated by density centrifugation 43
over a Lymphoprep gradient (Axis-Shield, Dundee, Scotland, UK) followed by washing in Hank’s 44
Balanced Salt Solution (Gibco BRL, Invitrogen, Life Technologies, Paisley, Scotland, UK). The PBMCs 45
were filtered through a pre-separation filter (Miltenyi Biotec, Bergisch Gladbach, Germany) and CD4+ 46
T cells were immunomagnetically isolated by negative selection using the CD4+ T cell isolation kit 47
(Miltenyi Biotec) using MS columns and a MiniMACS separator (Miltenyi Biotec) according to the 48
instructions provided by the manufacturer. 49
50
Fluorescence-activated cell sorting 51
3 The CD4+ T cells were labelled with mouse anti-human CD4-PeCy7 (clone SK3), CD45RA-V450 52
(clone HI100) and CD25-APC (clone M-A251; all from BD Biosciences) for 30 minutes (min) at 4°C in 53
the dark and washed in phosphate buffered saline (PBS, pH 7.4; Medicago, Uppsala, Sweden) 54
supplemented with 0.1% heat-inactivated fetal bovine serum (FBS; HyClone, GE Healthcare, Little 55
Chalfont, UK) by centrifugation at 500xg, 4°C for 5 min. CD4+ T cells were sorted into different T cell 56
subpopulations based on their expression of CD25 and CD45RA (Fig 1, A). Naive (CD4+CD25-CD45RA+) 57
and memory (CD4+CD25-CD45RA-) T conv cells, naive (CD4+CD25++CD45RA+) and memory 58
(CD4+CD25+++ CD45RA-) Treg cells were gated using a similar gating strategy as described by Miyara et 59
al.E2. The CD25+++ gate for memory Treg cells was based on the lowered expression of CD25 on naive 60
Treg cells (CD25++) which in turn was set to include cells with a lower CD25 expression whilst still 61
being positive. The CD25-gate for the Tconv cells was set to include a major proportion of the CD25 -62
cells while avoiding potential contamination of CD25dim -expressing cells. Naive (CD45RA+) and 63
memory cells (CD45RA-) were set based on the contour of the positive and negative populations. We 64
set stricter gates for both CD25 and CD45RA to ensure high purity of the sorted populations (Fig 1, 65
A). 66
The cells were sorted using the FACSAria III Cell sorter (BD Biosciences) with a 70 µM nozzle 67
and collected in PBS with 0.5% FBS. After sorting, the cells were centrifuged and lysed in Buffer RLT 68
Plus (Qiagen, Hilden, Germany) and stored at -70°C until RNA and DNA extraction. 69
70
RNA/DNA extraction and RT-PCR 71
RNA and DNA were extracted from the sorted cells using the Allprep DNA/RNA Micro Kit 72
(Qiagen, Hilden, Germany) according to the instructions provided by the manufacturer. RNA 73
concentrations were determined spectrophotometically (ND-1000, NanoDrop Technologies Inc, 74
Wilmington, DE, USA). The DNA concentration was determined with a fluorescence-based nucleic 75
acid method using a QuantusTM Fluorometer (Promega, Madison, WI, USA) with QuantiFluor Dye® 76
(Promega) according to the instructions provided by the manufacturer. 77
4 The levels of the δRec-ψJα signal joint TREC (sjTREC) were measured by TaqMan real-time 78
quantitative PCR utilizing previously validated primers and probes directed towards the signal joint 79
region of the TRECsE3-6. The PCR reaction was performed by mixing 4 µl of DNA (TREC) or 1 µl of DNA 80
(GAPDH) with 2x Taqman Universal Master Mix (Applied Biosystems, Foster City, CA, USA), together 81
with primers and probes for sjTREC (forward primer: 5´-CACATCCCTTTCAACCATGCT-3´; reverse 82
primer: 5´-GCCAGCTGCAGGGTTTAGG-3´ (both Invitrogen); probe: 6-FAM-5´-83
ACACCTCTGGTTTTTGTAAAGGTGCCCACT-3´-TAMRA; Applied Biosystems) or glyceraldehyde-3-84
phosphate dehydrogenase (GAPDH) (forward primer: 5´-GGACTGAGGCTCCCACCTTT-3´; reverse 85
primer: 5´-GCATGGACTGTGGTCTGCAA-3’; both Invitrogen); probe: VIC-5´-86
CATCCAAGACTGGCTCCTCCCTGC-3´-TAMRA; Applied Biosystems). The final concentrations of the 87
primers and probes in the reaction mixture were 500 and 300 nM for the TREC forward and reverse 88
primer respectively, 50 and 300 nM for GAPDH and 200 nM of both probes. 89
The mRNA expression of Foxp3, the lineage-specific transcription factor for Treg cells, was also 90
analyzed in a portion of the sorted T cell populations (Fig 1, B). RNA was converted to cDNA using the 91
high-capacity cDNA reverse transcription kit (Applied Biosystems) according to the instructions 92
provided by the manufacturer. Thermal cycling was carried out using the Arktik™ Thermal Cycler 93
(Thermo Scientific, Waltham, MA, USA). The reaction was carried out by mixing 4 µl (Foxp3) or 1 µl 94
(18S) of cDNA with 2x Taqman Universal Master Mix together with primers and probes (all from 95
Applied Biosystems) for Foxp3 (forward primer: GTGGCCCGGATGTGAGAA-3´; reverse: 5´-96
GCTGCTCCAGAGACGTACCATCT-3´; probe: FAM-5´-CCTCAAGCACTGCCAGGC-GGAC-3´-TAMRA) and 97
18S (forward primer: 5´-CGGCTACCACATCCAAGGAA-3´; reverse: 5´-GCTGGAATTACCGCGGCT-3´; 98
probe: FAM- 5’-TGCTGGCACCAGACTTG-CCCTC-3´-TAMRA) as previously usedE7, 8. The final 99
concentrations of the primers and probes in the reaction mixture were 300 and 900 nM for Foxp3 100
forward and reverse primer respectively, 200 and 100 nM for 18S and 200 nM (Foxp3) and 50 nM 101
(18S) of each probe. 102
5 All PCR amplifications were performed using the 7500 Fast Real-Time PCR system (Applied 103
Biosystems) with the thermal cycling conditions set to an initial step at 95°C for 20 seconds (s) 104
followed by 40 cycles at 95°C for 3 s and a final step at 60°C for 30 s. All samples were run in 105
duplicates. Baseline was set using the automatic baseline feature of the 7500 software version 2.3 106
(Applied Biosystems). Threshold values were adjusted manually and only samples with a Ct <35 were 107
considered detectable. Samples with a value above Ct 35, i.e. undetectable, were assigned a value of 108
Ct 35. TREC content in each sample was calculated using the delta Ct-method where the Ct values for 109
sjTREC were subtracted from the Ct values for the housekeeping gene GAPDH (formula 2Ct GAPDH-Ct 110
sjTREC), as previously describedE3. For Foxp3, the RNA content was normalized against the 111
housekeeping gene 18S rRNA and quantification was performed using the standard curve method. 112
113
Flow cytometry 114
Whole blood was stained with CD127-PerCP-Cy5.5 (clone HIL-7R-M21), CD45RA-V450 (clone 115
HI100), CD31-PeCy7 (clone WM59) and CD4-APC-Cy7 (clone SK3; all from BD Biosciences) for 30 min 116
at 4°C in darkness. Subsequently, the blood samples were incubated for 15 min at room temperature 117
in the dark with ammonium chloride (NH4Cl, diluted 1:10 with dH2O; Merck, Kenilworth, NJ, USA), for 118
lysis of the erythrocytes. The cells were washed in PBS supplemented with 0.1% FBS by 119
centrifugation at 500xg, 4°C for 5 min. The cells were fixed and permeabilized using the 120
Foxp3/Transcription Factor Buffer Staining Set (eBioscience, Thermo Fisher Scientific) according to 121
the instructions provided by the manufacturer. Briefly, the cells were fixed for 30 min at 4°C in the 122
dark and washed twice in permeabilization buffer and labelled with antibodies towards Ki67-FITC 123
(clone B56; BD Biosciences) and Foxp3-PE (clone PCH101; eBioscience, Thermo Fisher Scientific, 124
Waltham, MA, USA) for 30 min, 4°C, in the dark. The cells were then washed in permeabilization 125
buffer and resuspended in PBS with 0.1%FBS prior to flow cytometry analysis. To determine the 126
absolute cell count, a BD TruCountTM tube was used (BD Biosciences) as described by the 127
manufacturer. The TruCount tubes contain an exact number of beads that, when combined with a 128
6 known volume of blood, can be used to determine the concentration, i.e. the number of cells per 129
liter of blood, of different cell populations. Data was acquired using FACS Canto II (BD Biosciences) 130
and analyzed with Kaluza software version 1.2 (Beckman Coulter, Brea, CA, USA). 131
132
Gating and analysis 133
Lymphocytes were gated based on size (forward scatter) and granularity (side scatter), and 134
further characterized as CD4+. Treg and Tconv cell populations were defined based on their 135
expression of Foxp3 and CD45RA; naive (CD4+FoxplowCD45RA+) and memory (CD4+Foxp3highCD45RA-) 136
Treg cells, naive (CD4+Foxp3-CD45RA+) and memory (CD4+ Foxp3-CD45RA-) Tconv cells and non-137
suppressive Foxp3+ Th cells (CD4+ FoxpdimCD45RA-). The Foxp3high gate was set based on the lowered 138
expression of Foxp3 on naive Treg cells (Foxp3low), which in turn was gated to include cells that had a 139
lower Foxp3 expression while still being positive. The lack of Foxp3 expression (Foxp3-) was set based 140
on the contour of the naive Tconv cells. For gating strategy, see Fig E1 in this article’s Online 141
Repository at www.jacionline.org. The definition of naive and memory Treg cells was based on the 142
gating strategy described by Miyara et al.E2. To ensure that our gating strategy was correct, we added 143
CD127 in addition to Foxp3 to the definition of Treg cellsE2, which gave the same results, i.e. no 144
differences between pregnant and non-pregnant women (data not shown). Furthermore, more than 145
92% of the naive Treg cells were also CD127low. The naive Treg and Tconv cells were further gated for 146
CD31 expression based on the contour of the positive and negative populations. Ki67 expression in 147
Th subpopulations was set based on the expression in the whole CD4+ population. All gating was 148
performed in a blinded manner, i.e. the evaluator did not know the origin of the samples. 149
150
Statistical analysis 151
The majority of the flow cytometry data from the phenotyping and absolute counts followed 152
Gaussian distribution and differences between groups were therefore determined using one-way 153
ANOVA and Tukey’s multiple comparisons test. RT-PCR data was analyzed with Mann Whitney U test 154
7 and correlations between CD31 and TREC were performed using Spearman rank correlation. Flow 155
cytometry data is expressed as mean and standard deviation and RT-PCR data as median and 156
interquartile ranges. P-values ≤ 0.05 were considered statistically significant. Data was analyzed using 157
GraphPad Prism version 7.03 (GraphPad Software Inc). 158
159
Acknowledgements 160
We thank the midwives at the maternity care unit at Vrinnevi Hospital, Norrköping, Sweden, 161
for their invaluable help with recruiting and taking samples from the pregnant women included in the 162
study and the nurses at Clinical Immunology, Linköping University Hospital, for taking blood samples 163
from all the healthy controls. We also thank J. Raffetseder for help with the Foxp3 RT-PCR. 164
165
Reference list 166
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mice with thrombophilia. Am J Reprod Immunol 2015; 73:417-27. 169
E2. Miyara M, Yoshioka Y, Kitoh A, Shima T, Wing K, Niwa A, et al. Functional delineation and 170
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190 191
8 Table E1
192
Supplementary Table E1. Information about the participating women
Pregnant Non-pregnant
Subject characteristics 2nd trimester 3rd trimester
Number of subjects (n) 27 26 30
Age at inclusion (years) 28 (22-34) 28 (19-35) 27.5 (22-38)
Use of hormonal contraceptives (yes/no) N/A N/A 13/17
Menstrual cycle (luteal/follicular)a N/A N/A 11/15b
Smoking (yes/no) 1/26 0/26 0/30
Current pregnancy
Gestational age at inclusion (weeks) 26 (24-30) 36 (35-37) N/A
Parity week (weeks) 41 (40-43) 40.5 (38-43) N/A
Gender of baby (male/female) 15/12 13/13 N/A
Birth weight (g) 3550 (2735-4465) 3408 (2460-4710) N/A
Birth method (PN/VE/CS) 25/1/1 20/1/5 N/A
Pregnancy history
Previous pregnancies (n) 1 (0-4)* 1 (0-5)** 0 (0-2)
Previous births (n) 1 (0-3) 1 (0-4) 0 (0-2)
Data is shown as median and ranges (in parenthesis) or as categorical data. a Based on a 28-day menstrual cycle
b Four individuals on hormonal contraceptive reported not having a period.
*p<0.05, ** p<0.01 compared with healthy controls using Kruskal-Wallis with Mann Whitney test
N/A, not applicable.
PN, normal delivery; VE, vacuum extraction; CS, caesarean section. 193 194 195 196 197 198 199 200 201
9 Supplementary figure legends:
202 203
Figure E1. Gating strategy phenotyping by flow cytometry. (A) Subpopulations of CD4+ cells were 204
defined by CD45RA and Foxp3 expression and further analyzed for expression of (B) CD127, (C) CD31 205
and (D) Ki67. Representative flow cytometry dot plots from one individual are shown. MN, mature 206
naive; RTE, recent thymic emigrants; Treg, regulatory T cell. 207
208
Figure E2. Correlation between TREC levels and CD31 expression. TREC levels and CD31 expression 209
in (A) naive and memory Tconv cells (n=9), (B) naive and memory Treg cells (n=9). TREC levels were 210
determined by RT-PCR and CD31 expression was analyzed by flow cytometry. TREC, T cell receptor 211
excision circles; Tconv, conventional T cells; Treg, regulatory T cell. 212
213
Figure E3. Ki67 expression on CD4+ T cell subsets. Proportion of Ki67+ (A) mature naive and memory 214
Tconv and Treg cells and non-suppressive Foxp3+ Th cells, (B) RTE T conv cells and (C) RTE Treg cells, 215
analyzed by flow cytometry. Mean and standard deviations are shown. Missing values are due to 216
limited availability in cell numbers required to perform analysis. *P<0.05, ***P< 0.001, 217
****P<0.0001. NP, non-pregnant; P, pregnant; Tconv, conventional T cells; Treg, regulatory T cell. 218
219
Figure E4. Proportion of T cell subsets. Frequency of (A,B) mature naive Tconv and Treg cells, (C,D) 220
memory Tconv and Treg cells and (E) non-suppressive Foxp3+ Th cells, analyzed by flow cytometry. 221
Missing values are due to limited availability in cell numbers required to perform analysis. Mean and 222
standard deviations are shown. MN, mature naive; Tconv, conventional T cell; Treg, regulatory T cell. 223
