Watanabe et al.
Journal of Neuroinflammation(2024) 21:146
https://doi.org/10.1186/s12974-024-03144-1

Journal of Neuroinflammation

Open Access

RESEARCH

Differences in the characteristics
and functions of brain and spinal cord
regulatory T cells
Mahiro Watanabe1, Ako Matsui1, Natsumi Awata1, Ayame Nagafuchi1, Mio Kawazoe1, Yoshihiro Harada1 andMinako Ito1*

Abstract
T cells play an important role in the acquired immune response, with regulatory T cells (Tregs) serving as key players in immune tolerance. Tregs are found in nonlymphoid and damaged tissues and are referred to as “tissue Tregs”.
They have tissue-specific characteristics and contribute to immunomodulation, homeostasis, and tissue repair
through interactions with tissue cells. However, important determinants of Treg tissue specificity, such as antigen
specificity, tissue environment, and pathology, remain unclear. In this study, we analyzed Tregs in the central nervous system of mice with ischemic stroke and experimental autoimmune encephalomyelitis (EAE), a mouse modelof multiple sclerosis. The gene expression pattern of brain Tregs in the EAE model was more similar to that of ischemic
stroke Tregs in the brain than to that of spinal cord Tregs. In addition, most T-cell receptors (TCRs) with high clonality were present in both the brain and spinal cord. Furthermore, ­Gata3+ and ­Rorc+ Tregs expressed TCRs recognizing
MOG in the spinal cord, suggesting a tissue environment conducive to Rorc expression. Tissue-specific chemokine/
chemokine receptor interactions in the spinal cord and brain influenced Treg localization. Finally, spinal cord- or brainderived Tregs had greater anti-inflammatory capacities in EAE mice, respectively. Taken together, these findings
suggest that the tissue environment, rather than pathogenesis or antigen specificity, is the primary determinantof the tissue-specific properties of Tregs. These findings may contribute to the development of novel therapies to suppress inflammation through tissue-specific Treg regulation.
Keywords Tissue Tregs, EAE, Brain, Spinal cord
Introduction
Regulatory T cells (Tregs) are crucial for maintaining peripheral tolerance and tissue homeostasis in the
immune system. These cells express the master transcription factor FoxP3 and suppress excessive immune
responses by recognizing a variety of self-antigens andforeign antigens [1, 2]. Tregs in various nonlymphoid*Correspondence:
Minako Itominakoito@bioreg.kyushu-u.ac.jp
1
Division of Allergy and Immunology, Medical Institute of Bioregulation,
Kyushu University, 3‑1‑1 Maidashi, Higashi‑Ku, Fukuoka 812‑8582, Japantissues, such as fat, skin, lung, intestine, heart, and brain,
are termed “tissue Tregs” and play essential roles in tissue homeostasis and repair via tissue-cell interactions[3, 4]. They share common features, such as the IL-33
receptor ST2, the growth factor amphiregulin (Areg),and the anti-inflammatory cytokine IL-10 but also possess tissue-specific features, such as chemokine receptors, notch receptors, and neuropeptides [4]. After
accumulation in damaged tissues such as muscle, fat,and the brain through specific antigen recognition [5, 6],
their phenotype is thought to be influenced by the local
microenvironment. Single-cell RNA sequencing technology has shown that tissue Tregs gradually acquire their© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

characteristics in the corresponding lymph nodes andmature within the tissue [7–9].
In the context of central nervous system (CNS), brain
Tregs, similar to those from other tissues, are H­ elios+
thymic-derived Tregs (tTregs) with a specialized TCR
repertoire and high expression of CTLA-4, PD-1, Areg,
and ST2—molecules associated with immune suppression, tissue repair, and anti-inflammatory responses. Our
research shows that Tregs accumulate in the brain during
the chronic period two weeks after stroke onset and areimportant for the recovery of neurological symptoms [5].
Increasing the number of Treg cells by overexpressing
IL-2 in the IL-2:IL-2 antibody complex or astrocytes after
stroke restores neurological function in the long term[10]. These reports suggest that Tregs may be potential
therapeutic targets for neurological recovery after stroke.
Multiple sclerosis (MS) is an autoimmune disease inwhich autoreactive immune cells recognize and attack
the protective myelin sheath surrounding nerves in the
CNS. This causes irreversible damage that can impair
movement, muscle control, vision, and cognition.
Experimental autoimmune encephalomyelitis (EAE) isa representative model of MS characterized by paralysis
resulting from CNS inflammation, neuronal demyelination, axonal damage, and neurodegeneration. Tregs
produce IL-10 and TGFβ, which are important for EAE
recovery [11] and support myelin regeneration. They
directly signal glial precursors to differentiate into myelin-producing glial cells, which is a critical step in theremyelination process [12]. Tregs from patients withMS show defects in their suppressive capacity, including
decreased expression of several functionally important
genes, such as CTLA-4 and FoxP3, which may be responsible for disease development.
Thus, research on different tissue-specific Tregs has
progressed, and their characteristics have become clear.
However, the mechanisms by which each tissue Tregs
acquire these specific properties have not been determined, and the major determinants of Treg tissue specificity, such as antigen specificity, tissue environment, andpathology, have not yet been determined. In this study,
we aimed to elucidate the mechanism by which Tregs in
the CNS acquire tissue-specific properties by employing
a mouse model of ischemic stroke and EAE.

Methods
Mice

Wild-type C57BL/6J mice were purchased fromKBT Oriental (Breeder: Jackson Laboratory Japan).
­Foxp3hCD2KI mice, IL-17a-GFP mice and DEREG mice
were generated as described previously [26, 27]. All mice
were housed in a specific pathogen-free animal facility at Kyushu University with a 12-h light cycle. All the

Page 2 of 16

experimental procedures were reviewed and approved by
the Kyushu University Animal Experiment Committee,
and the care of the animals was in accordance with institutional guidelines.
Mouse model of ischemic stroke

Male mice aged 8–12 weeks and weighing 20–30 g wereused for focal brain ischemia experiments [5]. There wasno significant difference in weight or age between thewild-type mice and any of the knockout groups. We useda transient MCAO model constructed using an intraluminal suture. This transient suture MCAO model wasestablished as previously described [5]. The mice wereanesthetized with isoflurane in a mixture of 70% nitrous
oxide and 30% oxygen. During the MCAO procedure, thehead temperature was maintained at 36 °C using a heatlamp. Sixty minutes after MCAO, the brain was reperfused by removing the intraluminal suture. Neurological
function was evaluated using a previously described fourpoint scale neurological score method (0, no observable
deficit; 1, forelimb flexion; 2, decreased resistance to lateral push without circling; 3, same behavior as grade 2,
with circling) [28].
Mouse model of EAE
Immunization of ­MOG33‑55 peptides

Emulsions were prepared by mixing 200 μg of myelin
oligodendrocyte glycoprotein peptide (­MOG33-55) withcomplete Freund’s adjuvant plus M. tuberculosis. For
each mouse, 200 μg of the emulsion was injected subcutaneously into 3 sites on the back of F
­ oxp3hCD2KI and WT
mice (2–3 months old, female). Pertussis toxins (500 ng/body) were injected intraperitoneally twice, on days 0
and 2.
Clinical score scoring method

0: normal, 0.5: decreased tail tonus, 1: complete taildroop, 1.5: hind limb weakness, 2: incomplete hind limb
paralysis, 3: complete hind limb paralysis, 4: complete
hind limb paralysis including incomplete forelimb paralysis, 5: death.
Isolation of cells from the adult mouse brain and spinal
cordMice were perfused with PBS transcardially, and the cerebrum, cerebellum and spinal cord were removed. For
isolation of CNS Treg cells, the cerebrum, cerebellum
and spinal cord were minced and enzymatically dissociated with 2 mg/ml collagenase D (Roche Applied Science) and 1 mg/ml DNase I in RPMI-1640 for 30 min
at 37 °C. The digested tissue was centrifuged and resuspended in 37% Percoll (Cytiva) and centrifuged at 800 × g
for 20 min, after which the cell pellets were collected. The

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

isolated cells were stained with a fluorochrome-conjugated antibody. Fluorescein isothiocyanate (FITC), phycoerythrin (PE), peridinin chlorophyll protein-cyanine
5.5 (PerCP-Cy5.5), allophycocyanin (APC), PE-Cy7, and
APC-Cy7-conjugated antibodies were purchased from
BioLegend, BD or eBioscience. The primary antibodies used were as follows: anti-mouse CD45.2 antibody,anti-mouse CD11b antibody, anti-mouse CD3ε antibody,anti-human CD2 antibody, anti-mouse CD4 antibody,anti-mouse Areg antibody (R&D; BAF989), anti-mouse
ST2 antibody, and anti-mouse HTR7 antibody (Novus;
56,352), anti-mouse Rorgt, anti-mouse Gata3, antimouse IL-1R, anti-mouse CD25, anti-mouse Lag3, antimouse CXCR6, anti-mouse CCR8, anti-mouse CXCR4,
anti-mouse CD304 (Neuropilin1), and anti-mouse
Helios. The fixable viability dye eFluor 780 (FVD780) wasused to remove dead cells. The stained cells were sortedby FACSMelody, LSRFortessa (BD Biosciences) and
FlowJo software (Tree Star). The gating strategy for Tregs
was ­F VD−CD45.2+CD11b−CD3+CD4+Foxp3+. For Areg
staining, cells were stained after stimulation with eBioscience™ Cell Stimulation Cocktail (Thermo Fisher Scientific) for 3 h.
Immunohistochemistry

Mice were anesthetized by inhalation with isofluraneand perfusion was performed by injecting PBS into theleft ventricle. The lumber spinal cord segments were dissected and immersed in 4% paraformaldehyde (PFA) and
fixed at 4 °C for 24 h. For paraffin-embedded sections,the spinal cords in cassettes were prepared by the Laboratory for Research Support, Medical Institute of Bioregulation, Kyushu University. Samples were embedded inparaffin and cut into 5 µm sections. Samples on slides
were de-waxed in xylol and ethanol, antigen retrieval
was performed using boiled citrate buffer and samples were blocked for 1 h at room temperature (25 °C)
using Blocking One Histo (nacalai tesque). The sections
were incubated with primary antibodies included in
5% BSA/PBS overnight at 4 °C: rabbit anti-MBP (1:300;
Cell Signaling Technologies, 78,896), mouse anti-GFAP(1:500; Cell Signaling Technologies, 3670), goat anti-Iba1(1:300; FUJIFILM Wako Pure Chemical Corporation,
011–27991). After primary antibody incubation, sections were washed twice with PBS containing 0.1% Triton
X-100 (PBS-T) and once with PBS, and incubated withthe secondary antibody and Hoechst for 30 min at room
temperature: donkey anti-rabbit Alexa Fluor 647, donkey
anti-mouse Alexa Fluor 546, donkey-goat Alexa Fluor 488(all 1:300; Invitrogen), then washed with PBS-T and PBS.
Sections were sealed with cover glasses using PermaFluor
mounting medium (Thermo Fisher, TM-030-FM). The
images were taken with BZ-X700 (Keyence) and image

Page 3 of 16

analysis was performed using ImageJ. Statistical analysis
was performed in Prism9 (Graphpad).
In vivo depletion of Treg cells in EAE mice

DEREG or wild-type littermates were injected with diphtheria toxin (Merck) intraperitoneally at 20 μg/kg on days
13 and 15 after immunization with MOG. At day 17,these mice were sacrificed, and brains and spinal cords
were analyzed by flow cytometry.
Transferring Tregs into mice with EAE

EAE was induced in ­Foxp3hCD2KI mice, and Tregs were
sorted from the brain and spinal cord of EAE mice atday 23 after immunization. As a control, Tregs fromthe lymph nodes of untreated mice were sorted. These
Tregs (2 × ­104 cells) from the brain or spinal cord of 40­Foxp3hCD2KI mice were injected intravenously into WT
recipients 5 days after immunization, and neurologicalsymptoms were observed at the appropriate time points.
(Recipients of LN Treg: N = 14, EAE brain Treg: N = 14,
EAE SC Treg: N = 16).
For transfer experiment of Tregs after onset of EAE(Fig. S8), EAE was induced in F
­oxp3hCD2KI mice, andTregs were sorted from the brain and spinal cord of EAE
mice at day 23 after immunization. As control, Tregs
from the spleens of 4 CFA-treated mice were sorted.
These Tregs (2 × ­104 cells) from the brain or spinal cordof 34 ­Foxp3hCD2KI mice were injected intravenously into
WT recipients 17 days after immunization, and neurological symptoms were observed at the appropriate time
points. (Recipients of PBS: N = 6, CFA-treated SP Treg:
N = 6, EAE brain Treg: N = 7, EAE SC Treg: N = 6).
Chemokine array

EAE was induced in 2–3-month-old C57BL/6 J mice.
On day 23, after the mice were euthanized and perfusedwith PBS, the cerebrums and spinal cords were extracted
and crushed by a bead shocker for 20 s at 5,000 rpm
three times. The samples were centrifuged for 10 min at
15,000 rpm and 4 °C, after which the supernatants werecollected. A chemokine array was performed using theProteome Profiler Mouse Chemokine Array Kit (R&D;
ARY020) according to the manufacturer’s instructions.
The chemiluminescence signals on the membranes weredetected by ChemiDoc (Bio-Rad). The data analysis was
performed with Image Lab (Bio-Rad).
A migration assay was performed using a CytoSelect™
96-well cell of migration assay kit (Cell Biolabs; CBA105) according to the manufacturer’s instructions. Tregs
isolated from the brains or spinal cords of EAE mice
were seeded at 2 × ­104 cells/well in 10% FBS medium
Migration assay

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

supplemented with 0.2 mg/ml CCL6, CCL12, or CCL1
(BioLegend). At 4 h after seeding, the migrating cells
were lysed with lysis buffer/CyQuant® GR dye, and fluorescence was measured with an ­EnSpire® Multimode
Plate Reader (PerkinElmer).
TCR cloning and IL‑2 ELISATCR sequences were obtained from scTCR-seq information from brain or spinal cord Tregs and 2D2 or OT-II
mice. The DNA was synthesized by eBlocks Gene Fragments (IDT). The α and β chains were linked by the P2A
sequence and inserted into the pMX-IRES-GFP vector.
The retroviruses generated by these pMX-TCR-IRESGFP vectors were infected into TG40 cells. GFP-expressing cells were sorted by FACSMedoly and cocultured
with bone marrow-derived dendritic cells in media supplemented with ­MOG33-55 peptide (5 μg/ml), OVA peptide (200 μg/ml) or anti-CD3ε/CD28 antibodies (2 μg/ml) for 24 h. IL-2 in the supernatants was detected by amouse IL-2 ELISA kit (Invitrogen; 88–7024) according to
the manufacturer’s instructions.
RNA sequencing
Cell isolation and RNA extraction

Bulk RNA-seq of cerebrum, cerebellum and spinal
cord tissues from EAE mice: EAE was induced in 2- to
3-month-old C57BL/6J mice. On day 18 and 32 post
immunization, after the mice were euthanized, the cerebrum, cerebellum and spinal cord were extracted from 12
mice (day 18: pooled 3 mice × 2 samples, day 32: pooled 3
mice × 2 samples) and homogenized after PBS perfusion.
The tissues were homogenized in PBS by beads shocker(TOMY, MS-100). RNA was extracted from a portion of
the tissues using an RNeasy Mini Kit (QIAGEN).
Bulk RNA-seq of Tregs: ­Foxp3hCD2KI mice were induced
to experience ischemic stroke or EAE (stroke: male 4
mice × 2, EAE brain and spinal cord: female 4 mice × 2,
spleen: 2 mice × 2). At day 28 after ischemic stroke onset
or immunization, the mice were perfused with PBS,
and the brains and spinal cords were homogenized. The
immune cells were isolated using the methods describedin “Isolation of cells from the adult mouse brain and spinal cord”. Treg sorting was performed using a FACSAriaIII, and RNA extraction was performed using an RNeasy
Plus Micro Kit (QIAGEN).

Page 4 of 16

quality. For adapter trimming, Trim Galore! (v0.6.0) wasused. The sequence reads were mapped to the mouse reference genome GRCm38/mm10 from Ensembl (release102) using HISAT2 (version 2.2.1). The mapped reads
were counted for genes using featureCounts (v.2.0.0). The
data analysis was performed by iDEP.96. Differentiallyexpressed genes (DEGs) obtained between clusters were
subjected to Gene Ontology (GO) analysis using Metascape (v3.5).
Single‑cell RNA‑seq
Cell isolation

Two- to three-month-old C57BL/6 J mice were subjected
to EAE or cerebral infarction. After the mice were euthanized, the cerebrum, cerebellum, spinal cord and lymph
nodes were removed by PBS perfusion and homogenized.
Staining was performed with the following antibodies:anti-CD45.2, anti-CD11b, anti-hCD2, anti-CD3ε, andanti-CD4. Totalseq hashtag antibody (BioLegend) was
then reacted with each sample, and Tregs were sortedwith a FACSMelody (BD Biosciences).
Library preparation and NGS

Libraries were prepared according to the protocol of
the Chromuim Next GEM Single Cell 5’ Reagent Kits v2(Dual Index, 10 × Genomics, Pleasanton, CA, USA) usinga Chromium controller (10 × Genomics). Briefly, GEMs
were prepared by loading barcoded Single Cell VDJ 5’ Gel
Beads, master mix containing cells and RT enzymes, andOil onto Chromium Next GEM Chip K. Barcoded cDNA
was subsequently generated from the GEM. The cDNA
was amplified via PCR to generate V(D)J, 5’ Gene Expression and Feature Barcode libraries. Sequencing was thenperformed using a NovaSeq 6000 (Illumina, San Diego,
CA, USA) at the Laboratory for Research Support of theInstitute of Bioregulatory Medicine, Kyushu University.
Preprocessing

Fastq files were generated from the NGS data using
Cell Ranger (v6.1.2) (10 × Genomics). The c.loupe files(gene expression) and v.loupe files (TCR sequence)
were obtained from Cell Ranger Multi (mouse genome;
Genome Reference Consortium Mouse Build 38, mm10).

RNA sequencing

Library preparation was performed using NEBNext
PolyA stranded Ultra II Directional RNA Library Prep
(New England BioLabs, MA) by Azenta. The libraries
were sequenced on Illumina NovaSeq 6000 sequencers(Illumina, San Diego, CA). Sequence reads in FASTQ format were applied to FastQC (v0.11.4) to assess sequence

4Data analysis

The Loupe Browser (v7.0.1) and Loupe V(D)J Browser(v5.1.0) were used to analyze gene expression and the
TCR repertoire. Differentially expressed genes (DEGs)
obtained between clusters were subjected to Gene Ontology (GO) analysis using Metascape (v3.5).

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

Statistics

All the experiments were performed with at least two
biological replicates and yielded comparable results
except for the scRNA-seq experiment, which was conducted only once. Sample sizes were determined basedon previous similar experiments [5] but were not predetermined by any statistical methods. The data areexpressed as the mean ± s.e.m. Statistical significancewas determined by one-way or two-way analysis of variance (ANOVA) followed by post hoc Tukey’s multiple
comparisons test to analyze differences among three ormore groups and by unpaired Student’s t test to analyze
differences between two groups. P < 0.05 was considered
to indicate a significant difference (*p < 0.05; **p < 0.01;***p < 0.001; ****p < 0.0001; ns, not significant). All the statistical analyses were performed with GraphPad Prism(version 9.5.1).

Results
Tregs prevent the worsening of neurological symptoms
in EAE mice

We previously reported that Tregs contribute to therecovery of neurological symptoms after ischemic stroke[5]. To investigate whether Treg dysfunction or absence
was also involved in pathologies other than ischemic
stroke, we induced EAE in DEREG mice. These miceexpress the diphtheria toxin receptor under the controlof the Foxp3 gene promoter/enhancer [13]. The depletionof Tregs by the administration of diphtheria toxin post
onset resulted in the exacerbation of neurological symptoms (Fig. 1A, S1A), indicating the importance of Tregs
in suppressing the progression of EAE.

Page 5 of 16

The EAE model used in this study is initially induced
through spinal cord inflammation, followed by subsequent damage to the brain. We examined the characteristics of Tregs in the brain and spinal cord of mice with
EAE and found that the expression levels of Areg, known
tissue Treg marker, were high in both the brain and spinal cord, whereas that of HTR7, which we identified asa brain Treg marker, was high only in the brain (Fig. 1B).
However, the number of A
­ reg+, ­HTR7+ Tregs was higher
in the spleen due to the overwhelmingly higher numberof Tregs in the spleen (Fig. S1B). These results indicatethat Treg characteristics differ between the brain and thespinal cord, even in mice with the same pathology.
Analysis of CNS Tregs in mice with stroke and EAE

Next, gene expression analysis of CNS Tregs fromischemic stroke and EAE mice (brain and spinal cord
separately) was performed to determine their pathology- and tissue-specific characteristics. We sorted CNS
Tregs and performed bulk RNA-seq analysis (Fig. S2A,
B). Principal component analysis (PCA) of bulk RNA-seq
data revealed that Tregs in the brain and spinal cord havedifferent characteristics from those in the spleen, a secondary lymphoid tissue, and that EAE brain Tregs weremore similar to brain Tregs in ischemic stroke than spinal cord Tregs in EAE (Fig. 2A). Enrichment analysis ofgenes characterizing PCA eigenvectors confirmed thatgenes related to the nervous system and cytokines are
key variables (Fig. S2C). A heatmap revealed many genesthat were specifically expressed in EAE spinal cord Tregs(Fig. 2B).
To clarify the differences between brain and spinal cord
Tregs, we used Gene Ontology (GO) analysis to classify

Fig. 1 Effect of Tregs on the recovery of neurological symptoms in EAE mice. A Neurological score of EAE-induced WT (N = 3) or DEREG (N = 6) micetreated with diphtheria toxin at 13 and 15 days after immunization with MOG. B Flow cytometric analysis of Tregs in the brain, spinal cord of EAE
model mice (N = 6) at day 24, lung and spleen of control mice (N = 6). The data are representative of at least two independent experiments. P values
were determined by two-way ANOVA (A) and one-way ANOVA (B). The data are shown as the mean ± s.e.m. SC: spinal cord

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

Page 6 of 16

Fig. 2 Characterization of Tregs in the brain and spinal cord by bulk RNA-seq. A, B PCA (A) and heatmap (B) of bulk RNA-seq analysis of Tregs
from brain and spinal cord of ischemic or EAE ­Foxp3hCD2KI mice at day 28 and Tregs from spleen of control ­Foxp3hCD2KI mice (N = 2, pooled from 4
animals for each replicate). C, D Heatmap (C) and bar graph (D) of Gene Ontology (GO) analysis results for the DEGs in the four clusters and the top
5 GO terms. E The expression levels of Gata3 and Rorc in Tregs determined from bulk RNA-seq data of the indicated tissue Tregs

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

the genes into four clusters: Cluster A, specific for spleen
Tregs; Cluster B, specific for brain Tregs in stroke and
EAE; Cluster C, highly expressed in all CNS Tregs instroke and EAE; and Cluster D, highly expressed in spinal
cord Tregs only (Fig. 2C). Brain Treg-specific Cluster B
exhibited increased expression of genes related to nervous system development (including Htr7) and cell differentiation (Efnb2, Spi1, and Gata3). Cluster C included
genes characteristic of tissue Tregs, such as Nr4a1,
Nr4a2, Nr4a3, Il10, Rora, Nfil3, Pparg, and Il1rl1. Cluster
D showed an increased expression of genes such as Rorc
and Il17f (Fig. 2D, S2D). The expression levels of Gata3
and Rorc were considered representative of genes thatdiffered between the brain and spinal cord (Fig. 2E). Thus,
these results reveal distinct gene expression patterns
between brain and spinal cord Tregs within the same
CNS. This suggests that some Treg characteristics may be
more similar in the same tissue in different pathologies
than in different tissues in the same pathology.
Next, scRNA-seq was performed to eliminate the possibility of contamination from tissue resident cells during
sorting and to compare gene expression at the cellularlevel. Uniform manifold approximation and projection(UMAP) showed that EAE brain Tregs had different
characteristics from EAE spinal cord Tregs but weresimilar to stroke brain Tregs (Fig. 3A). When the Treg
population was divided into four clusters, most EAE andischemic brain Tregs were in Cluster 1, whereas mostspinal cord Tregs were in Cluster 2 (Fig. 3B). A heatmap
illustrating the comparison of differentially expressed
genes between the clusters highlighted genes specific tobrain or spinal cord Tregs (Fig. 3C). Enrichment analysis revealed that Cluster 1 had high expression of genes
related to growth factors and negative regulation of theimmune system, whereas Cluster 2 had high expressionof genes related to T cell activation (Fig. 3D). Differencesin Treg cell function mediated by transcription factors
have been reported [14]. According to the analysis of
the gene expression of transcription factors involved inT-cell subtype classification, Foxp3, a master regulatory
gene of Tregs, was highly expressed across all groups andwas expressed at similar levels in Tregs (Fig. 3E, F). Additionally, the expression of Tbx21, a regulator of the Th1
cytokine interferon gamma (IFN-γ), and Rorc, which isPage 7 of 16

involved in IL-17a expression, was elevated in EAE spinal cord Tregs (Fig. 3E, F, S3A). On the other hand, brain
Tregs presented increased expression of Gata3, a transcription factor important for tissue Tregs and Th2 cells,
along with genes that antagonize effectors such as Klf2
and Klf6 [15] (Fig. 3E, F). These results suggest that brain
and spinal cord Tregs have distinct characteristics.
TCR analysis of the brain and spinal cord of EAE mice

To investigate whether antigen specificity is a criticalfactor in shaping Treg properties, we performed scTCRseq analysis of CNS Tregs from EAE mice. The results
showed that TCRs with high clonality were present inboth the brain and spinal cord (Fig. 4A). We focused on
the top six TCR sequences in the spinal cord and examined the cells expressing these TCRs. ­Rorc+ Tregs (Nos.
1, 4, and 6) were detected in the spinal cord but rarelyin the brain. In contrast, ­Gata3+ Tregs (Nos. 2, 3, and5) were frequently detected in both the brain and spinal
cord (Fig. 4B, C). ­Gata3+ Tregs are tTregs that recognize
self-antigens, whereas ­Rorc+ Tregs are peripheral Tregs(pTregs) derived from naïve T cells influenced by gut
bacteria and dietary antigens in the intestinal tract [16–19]. Therefore, we hypothesized that ­Gata3+ and ­Rorc+
Tregs recognize different antigens and cloned TCRs to
identify these antigens. We performed in vitro culture
experiments expressing the TCR of Treg on TCR-deleted
T cell hybridomas producing IL-2 in response to TCR
stimulation. Contrary to our expectations, however, both­Gata3+ Tregs and R­ orc+ Tregs responded to the myelin
oligodendrocyte glycoprotein (MOG) peptide, except
for No. 3 (No. 4 was excluded because the cloned TCR
did not appear on the T cell surface), suggesting that
although CNS antigens are required for CNS infiltration,
the observed differences in properties are not antigen
dependent (Fig. 4D).
Since it has been suggested that Rorγt-positive Tregs
are pTregs [19], we hypothesized that the spinal cord has
a tissue environment conducive to R
­ orc+ Tregs and investigated their origin as either tTregs or inducible pTregs.
The low expression of Nrp1 and Ikzf2 (Helios), which aretTreg markers, in ­Rorc+ Tregs suggested that these cells
were likely inducible Tregs (Fig. 4E, S4A, B). The genes
involved in the induction of Rorc expression (Tgfb1, Il6,

(See figure on next page.)
Fig. 3 Characterization of Tregs in the brain and spinal cord by scRNA-seq. A-F scRNA-seq data of Tregs derived from EAE ­Foxp3hCD2KI mice (N = 4)
at day 23. Uniform manifold approximation and projection (UMAP) visualization of scRNA-seq data of Tregs divided by the ischemic brain, EAE
brain, and EAE spinal cord (A). UMAP plot of scRNA-seq data for Tregs divided into 4 clusters and a bar plot of the percentage of clusters (B). Gene
expression heatmap of the signature genes per cluster. This figure shows only cluster 1 and cluster 2 (C). GO analysis of DEGs in cluster 1 and cluster
2 (D). Feature plot (E) and violin plot (F) of the expression levels of several genes, including those of the transcription factors Foxp3, Tbx21, Rorc,
and Gata3, in Tregs in the brain or spinal cord

Watanabe et al. Journal of Neuroinflammation

Fig. 3 (See legend on previous page.)(2024) 21:146

Page 8 of 16

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

Il1b, and Il23) tended to be more highly expressed in the
spinal cord than in brain tissue, whereas those involved
in Gata3 expression (Il33 and Il2) showed no significant
difference between the two tissues (Fig. 4F). Furthermore, the expression of their receptors on Tregs suggested that Il1r1 and Il23r were expressed on R
­ orc+ Tregs(Fig. 4G, S4C). Differences in gene expression between
the spinal cord and brain were also detected for ­Gata3+
Tregs; Ier5l and Lag3 were highly expressed in spinal
cord ­Gata3+ Tregs; and Egr1, Klf2 and Jun were highly
expressed in brain Tregs (Fig. 4H, S4C) (some genes areincluded in Fig. 3C). These ­Gata3+ Tregs have the same
TCR but different characteristics depending on the localized tissue, suggesting the importance of the environment, including chemokines and cytokines, rather thanantigen specificity.
Spinal cord Tregs and brain Tregs have different chemokine
receptors

Next, we investigated the relationship between
chemokine receptors on Tregs and chemokines in the
spinal cord and brain. Bulk RNA-seq, scRNA-seq andflow cytometry analysis revealed that Ccr1, Ccr2, Cxcr6
and Ccr8 were highly expressed as chemokine receptors on spinal cord Tregs, whereas Cxcr4 was highly
expressed on brain Tregs (Fig. 5A, S5A-D). To investigate the relationship between Treg localization andchemokine receptors over time, we performed scRNAseq analysis of Tregs in the cerebrum, cerebellum, andspinal cord during the peak and recovery phases of EAE
symptoms (Fig. 5B). From the peak phase onward, thepercentage of Tregs in the cerebrum was greater thanthat in the spinal cord, and it increased throughout the
CNS during the recovery phase (Fig. 5C). At the time ofhigh inflammation on day 18 post EAE induction, theexpression of chemokine receptors, such as Ccr1, Ccr2,
Ccr6, and Cxcr6, was high in spinal cord Tregs, and on
day 32 during the recovery period, Ccr8 and Cxcr4 werehighly expressed in the brain and spinal cord (Fig. 5D).
In the spinal cord, ­Rorc+ Tregs were observed during
inflammation (Fig. 5D).

Page 9 of 16

Tissue Tregs migrate to target tissues after tissue
antigens are presented to their lymph nodes [8]. Using
scRNA-seq analysis, the expression of Rorc or Gata3 andthe clonotype frequencies of TCRs were investigated in
the CNS (cerebrum, cerebellum and spinal cord) and inlymph nodes near the spinal cord (superficial cervical,
deep cervical, axillary, mediastinal, renal and lumbar) on
day 18 or day 32 after EAE induction (Fig. S6A). Common TCRs between the brain, spinal cord and lymph
nodes were detected, and Rorc or Gata3 expression was
found to be independent of the clonotype of the TCR.
On EAE day 18, Rorc-expressing Tregs were found to
the similar extent of Gata3-expressing cells in populations expressing TCRs, and high clonality was detectedin the CNS, especially in the spinal cord (Fig. S6B). On
day 32 after EAE, the number of populations expressing Rorc was smaller than that of those expressing Gata3(Fig. S6C). In both phases, Rorc expression was scarcely
detected in Tregs in the lymph nodes, except for the cervical lymph nodes. These results suggest that R­ orc+ Tregs
are induced during the acute phase of EAE in the spinal
cord rather than in the lymph nodes, independent of thespecific antigen.
Next, to examine chemokine expression in the tissues,
we performed bulk RNA-seq analysis of the cerebrum,
cerebellum, and spinal cord and revealed differences ingene expression in the tissues during the highly inflammatory (day 18) and recovery (day 32) periods (Fig. 5E).
The spinal cord exhibited the most inflammation, followed by the cerebellum, while the cerebrum exhibitedthe least inflammation. Interestingly, the patterns of gene
expression in the spinal cord on day 32 and in the cerebellum on day 18 were similar (Fig. 5E). The expression of
Ccl6, Ccl12, and Cxcl16, the ligands for Ccr1, Ccr2, andCxcr6, respectively, was high in the spinal cord on day
18 but decreased during the recovery phase. In contrast,
the cerebrum had high expression of Ccl8, the ligand for
Ccr8, and Cxcl12. The expression of Cxcl12 increasedin the cerebrum, cerebellum, and spinal cord during therecovery period (Fig. 5F, G). Additionally, the cerebellum,
which is located between the spinal cord and cerebrum,
exhibited intermediate expression (Fig. 5F). According(See figure on next page.)
Fig. 4 TCR analysis of the brain and spinal cord of EAE mice. A–C TCR repertoire analysis of brain and spinal cord Tregs from EAE ­Foxp3hCD2KI
mice (N = 4) at day 23. The plot of the percentage of shared clonotypes between the brain and spinal cord (A). Feature plot of the top six TCR
clonotypes shared between the brain and spinal cord (B). The sequences of the top six TCR clonotypes shared between the brain and spinal cord
(C). D The protein levels of IL-2 in the supernatants of the top six TCR-induced TG40 cells stimulated with ­MOG33-55 peptide (5 μg/ml), OVA peptide(200 μg/ml) or anti-CD3ε/CD28 antibodies (2 μg/ml) for 24 h. E Feature plot of tTreg markers such as Nrp1 and Ikzf2. F The expression levels of Rorc
or Gata3 inducible cytokine genes in bulk RNA-seq data from cerebrum or spinal cord tissues derived from EAE F­ oxp3hCD2KI mice at 18 or 32 days
after immunization with MOG peptide (day 18 and day 32: N = 2, pooled from 3 animals for each replicate). G Feature plot of cytokine receptor
genes in (F). H Feature plot of DEGs between brain ­Gata3+ Tregs and SC ­Gata3+ Tregs. For (D), data are representative of at least three independent
experiments. P values were determined by two-tailed Student’s t test (F). The data are shown as the mean ± s.e.mWatanabe et al. Journal of Neuroinflammation

Fig. 4 (See legend on previous page.)(2024) 21:146

Page 10 of 16

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

to the results of a chemokine-induced migration assay,
spinal cord Tregs tended to migrate more in response to
Ccl6 and Ccl12 than brain Tregs. In contrast, Ccl1, theligand for Ccr8, induced migration of both brain and spinal cord Tregs (Fig. 5H). These results suggest that differences in chemokine expression in the brain and spinal
cord may be a determining factor in the characteristics ofinfiltrating Tregs.
Tissue‑specific Tregs have tissue‑specific anti‑inflammatory
and reparative effects

To examine the effect of brain and spinal cord Tregs on
EAE symptoms, we performed a transfer experimentusing Tregs from EAE mice. Tregs from the spinal cord of
EAE mice showed a significant alleviation of symptoms
compared to Tregs from untreated lymph nodes (Fig. 6A,
S7A). In addition, brain Tregs had an ameliorative effectthat was intermediate between the effects of spinal cord
and lymph node Tregs (Fig. 6A). Analysis of the recipient’s brain, spinal cord, and lymph nodes revealed adistinct migratory pattern of Tregs depending on theirtissue of origin. Specifically, Tregs originating from thebrain were found to preferentially migrate to the brain,
whereas those derived from the spinal cord exhibited ahigher propensity to migrate to the spinal cord (Fig. 6B).
The phenotype of the transferred Tregs was more positive for Helios in Tregs in brain tissue than in Tregs inspinal cord tissue (Fig. S7B). To determine whether Tregs
are more important in suppressing disease progression or tissue repair, we transferred Tregs at the peak of
EAE symptoms and examined the contribution of Tregs
to recovery from EAE. We found that transplantation ofTregs did not contribute to the recovery of neurologicalscores, but suppressed microglial and astrocyte activation (Fig. S8A, B). These result, combined with the factthat transplantation of Tregs prior to disease onset inhibits disease onset and progression (Fig. 6A), suggests that
Treg transplantation may be more effective in reducing
inflammation than in tissue repair. These data suggestthat spinal cord Tregs are more likely to infiltrate the spinal cord and promote tissue protection in a tissue-specific manner after infiltration.

Page 11 of 16

Discussion
Although detailed characterization of Tregs in tissues,
such as the gut, has been reported, differences in thecharacteristics of Tregs in the CNS have not been elucidated. In this study, we clarified the differences in Treg
phenotypes between the brain and spinal cord using a
CNS disease model of ischemic stroke and EAE (Fig. 6C).
The importance of Tregs in CNS diseases has been
demonstrated by the exacerbation of the neurologicalsymptoms of ischemic stroke and EAE in the absence ofTregs in DEREG mice or CD25 antibodies [5, 20]. Moreover, Tregs have also shown symptomatic ameliorative
effects on other neurological diseases, such as Parkinson’s disease and amyotrophic lateral sclerosis [21–23].
Therefore, it is necessary to understand the different
characteristics of Tregs to develop Treg-mediated disease
therapies.
Gene expression analysis of brain and spinal cord Tregs
from stroke and EAE mice revealed that these cells are
more similar to each other than to spleen Tregs but havedifferent properties in each tissue and pathological condition. GO enrichment analysis showed that the genes
could be divided into clusters based on their distinct
expression in the brain and spinal cord after stroke andin EAE, suggesting that differences in the tissue environment are more important than pathological conditions.
Furthermore, analysis of the TCRs of brain and spinal
cord Tregs in EAE revealed that highly clonal TCRs arepresent in both tissues, suggesting that the tissue environment is more important for the acquisition of tissuespecific properties than is the disease state or antigen
specificity.
Tissue Tregs can be epigenetically modified by priming with tissue antigens in secondary lymphoid tissues [6–9]. Tregs infiltrating the brain and spinal cord
may recognize and clonally proliferate MOG and otherautoantigens, but no other self-antigens were identified in this study. Moreover, the presentation of selfantigens may be necessary for Treg survival in the CNS.
Thus, given the potential for tissue infiltration by priming with autoantigens in secondary lymphoid tissues,
antigen specificity is important in the early stages of the(See figure on next page.)
Fig. 5 Differences in chemokine-chemokine receptor interactions. A scRNA-seq data of Tregs derived from EAE ­Foxp3hCD2KI mice (N = 4) at day
23. Feature plot of chemokine receptors associated with DEGs between brain Tregs and spinal cord Tregs in Tregs. B–D ­Foxp3hCD2KI mice (day18: N = 6, day 32: N = 6) were subjected to EAE. Cerebrum, cerebellum, and spinal cord Tregs were sorted at 18 and 32 days after immunization.
Neurological score of EAE mice (B). Flow cytometric analysis of the percentage of Tregs among ­CD4+ T cells in the cerebrum, cerebellum, and spinal
cord (C). Dot plot of chemokine receptors on Tregs (D). E, F PCA (E) and expression levels of chemokines (F) determined via bulk RNA-seq analysisof the cerebrum, cerebellum, and spinal cord in mice (N = 2, pooled from 3 animals for each replicate) of B–D. G Chemokine array analysisof brain or spinal cord lysates from untreated or EAE mice at day 23 (N = 3). H Migration of brain or spinal cord Tregs derived from EAE ­Foxp3hCD2KI
mice at day 22 in the presence of CCL6, CCL12 or CCL1. For (H), data are representative of at least two independent experiments. P values were
determined by two-tailed Student’s t test (cerebrum vs. spinal cord) (E). The data are shown as the mean ± s.e.mWatanabe et al. Journal of Neuroinflammation

Fig. 5 (See legend on previous page.)(2024) 21:146

Page 12 of 16

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

Page 13 of 16

Fig. 6 Therapeutic effects of spinal cord Tregs on EAE mice. A, B Lymph node Tregs from control F­ oxp3hCD2KI mice, brain Tregs or spinal cord Tregs
derived from EAE ­Foxp3hCD2KI mice at day 23–25 were injected intravenously in EAE wild-type mice at day 5. Neurological scores of EAE wild-typemice (EAE brain Treg; N = 14, EAE spinal cord Treg; N = 16, Lymph node Treg; N = 14). The data were pooled from two independent experiments.
P values were determined by two-way ANOVA. The data are shown as the mean ± s.e.m (A). Flow cytometric analysis of Tregs in the brain, spinal
cord or lymph node derived from Tregs-transferred mice (EAE brain Treg; N = 2, EAE spinal cord Treg; N = 5, Lymph node Treg; N = 4). The data arerepresentative of at least two independent experiments. P values were determined by one-way ANOVA. The data are shown as the mean ± s.e.m (B).
C Schematic model showing the difference of Treg phenotype between brain and spinal cord. SC: spinal cord, LN: lymph node

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

acquisition of tissue-specific phenotypes. The fact that
­Rorc+ and ­Gata3+ Tregs recognize the same MOG peptide for antigens but have different TCR sequences suggests that the TCR is one of the determinants of theseproperties.
In ­Gata3+ Tregs, GATA3 stabilizes FOXP3 expression,
enhances its inhibitory capacity and allows tissue-specific expression of homing receptors, which are involvedin suppressing inflammation in the kidney and skin andsuppressing fibrosis in Th2 responses [14, 24]. In theintestinal tract, R­ orc+ Tregs induced from naïve T-cells
by gut bacteria and dietary antigens play a major role
[16, 18, 19]. ­Rorc+ Tregs are present in the spinal cord
in EAE, however, they are rarely present in the brain.
This may be because the spinal cord has an environment(e.g., expression of IL-6, IL-1β, IL-23, and TGFβ) that can
induce and maintain ­Rorc+ Tregs, whereas the brain maylack such an environment. Another important factor that
determines the localization of tissue Tregs is that somechemokines are expressed in the brain and spinal cord,
while others are different, and there are also differencesin the chemokine receptors on Tregs.
Changes in the types and characteristics of immune
cells in the brain and spinal cord occur over time after
EAE or stroke. Therefore, the tissue-specific properties of the brain and spinal cord observed in this study
may be transient. From the onset to the peak of symptoms, the Th17 response is strong, and chemokines that
attract ­Rorc+ Tregs, especially those in the spinal cord,
are highly expressed. However, the expression of thesechemokines is low in the brain. Chemokine receptors,
such as Cxcr6, which are highly expressed on almost all
CNS Tregs during EAE induction, may be used to infiltrate the spinal cord and are subsequently attracted bychemokines that are highly expressed in the brain. It is
possible that after migrating to the brain, their phenotype
can change according to the environment. However, theexact routes of infiltration into the brain and spinal cord
remain unclear.
We also analyzed the distribution of Tregs in the lymph
nodes and the CNS. These results suggested that in theearly stage of inflammation, Tregs undergo antigen presentation in the axillary and renal lymph nodes and infiltrate the spinal cord. This may be due to the possibilityof antigen presentation in the lymph nodes where the
MOG-containing emulsion was injected subcutaneously.
Subsequently, Tregs expressing the same TCR as CNS
Tregs were detected in the deep cervical lymph nodes,
possibly because of their connection with the lymphatic
vessels of the dura covering the brain.
The transfer of Tregs isolated from the spinal cordand brain strongly alleviated neurological symptoms inthe same tissue as was observed in the isolated tissue,

Page 14 of 16

suggesting a tissue-specific suppressive effect. However, it
is unclear whether this difference is due to the number of
infiltrating Tregs or tissue-specific repair factors. Recent
advances in the study of tissue Tregs have revealed thatthey not only suppress inflammation but also express avariety of characteristic genes, including tissue-specificrepair factors and factors that promote stem cell differentiation [4, 25]. The identification of Treg-derived repair
factors through a more comprehensive analysis will likely
lead to the discovery of potential therapeutic molecules
for neuroinflammatory and neurodegenerative diseases.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12974-​024-​03144-1.
Additional file 1. Fig. S1 Effect of diphtheria toxin on DEREG mice and thenumber of tissue Tregs. A Flow cytometric analysis of EAE brain and EAEspinal cord Tregs in DEREG mice (N = 3) or wild-type mice (N = 4) at day 17.
B Flow cytometric analysis of brain or spinal cord Tregs derived from EAE­Foxp3hCD2KI mice at day 24 (N = 6) and lung or spleen Tregs from control
mice. The data are representative of at least two independent experiments. P values were determined by two-tailed Student’s t test. The data
are shown as the mean ± s.e.m. SC: spinal cord
Additional file 2. Fig. S2 The analysis of bulk RNA-seq of Treg. A Tregs
were sorted from ischemia ­Foxp3hCD2KI mice brain at day 23 (N = 4) or
MOG-treated ­Foxp3hCD2KI mice brain and spinal cord at day 23 (N = 4).
Flow cytometry dot-plots show gating strategy for defining Tregs. B–D
Bulk RNA-seq data of brain Tregs or spinal cord Tregs derived from EAE­Foxp3hCD2KI mice at day 28 and spleen Tregs from control mice. Gene
expression level of Treg markers (B). Enrichment analysis of the genes thatcharacterize the PCA eigenvectors in main Fig. 2A (C). Gene expression
level of marker genes in cluster C and D in Fig. 2C (D)
Additional file 3. Fig. S3 The protein expression of transcription factor of
Treg. Flow cytometric analysis of brain or spinal cord Tregs derived from
EAE ­Foxp3hCD2KI mice at day 27 (N = 3, pooled from 12 animals for each
replicate). P values were determined by two-tailed Student’s t test. The
data are shown as the mean ± s.e.m. SC: spinal cord
Additional file 4 Fig. S4 The protein expression of tTreg markers andreceptors of Tregs. A–C Flow cytometric analysis of brain or spinal cord
Tregs derived from EAE ­Foxp3hCD2KI mice at day 27 (N = 3, pooled from
12 animals for each replicate). tTreg markers (Helios and Nrp1), RORγt,cytokine receptors (IL1R, ST2 and CD25) and LAG3 were detected. P values
were determined by two-tailed Student’s t test. The data are shown as themean ± s.e.m. SC: spinal cord
Additional file 5. Fig. S5 The protein expression of chemokine receptorsof Tregs. A, B Volcano plot showing DEG from bulk RNA-seq data of brain
Tregs or spinal cord Tregs derived from EAE ­Foxp3hCD2KI mice (N = 2,pooled from 4 animals for each replicate) at day 28 (A) and scRNA-seq
data of Tregs derived from EAE ­Foxp3hCD2KI mice (N = 4) at day 23 (B). C
The expression level of chemokine receptors in the brains or spinal cords
derived from mice shown in (A). Spleen Tregs were sorted from control­Foxp3hCD2KI mice. The data are shown as the mean ± s.e.m. D Flow cytometric analysis of brain or spinal cord Tregs derived from EAE ­Foxp3hCD2KI
mice at day 24 (N = 3, pooled from 2 animals). Right bar graphs wereobtained by left representative histograms. P values were determined by
two-tailed Student’s t test. The data are shown as the mean ± s.e.m. SP:
spleen, SC: spinal cord
Additional file 6. Fig. S6 Rorc or Gata3 expression pattern in Tregs expressing CNS or lymph node TCRs in EAE mice. A Schematic representationof the investigated lymph nodes. B, C Analysis of the TCR repertoire andgene expression using scRNA-seq at EAE day 18 (B) or day 32 (C) after
immunization. The left images show the clonotype frequency of the TCRs.

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

The right images represent tissue-specific Rorc and Gata3 expression patterns according to TCR clonotype
Additional file 7. Fig. S7 Tregs sorting by flow cytometry. A Tregs were
sorted from MOG-treated ­Foxp3hCD2KI mice brain or spinal cord at EAE day
23 (N = 34) or CFA-treated F­ oxp3hCD2KI mice spleen (N = 4). Flow cytometry
dot-plots show gating strategy for defining Tregs. B Flow cytometricanalysis of transferred brain or SC Tregs. Brain Tregs and SC Tregs sorted
from EAE F­ oxp3hCD2KI mice at day 28 were injected intravenously in EAE
wild-type mice at day 5. Brain cells in brain Treg-injected mice and spinal
cord cells in spinal cord Treg-injected mice were analyzed by flow cytometry. P values were determined by two-tailed Student’s t test. The data areshown as the mean ± s.e.m. SP: spleen, SC: spinal cord
Additional file 8. Fig. S8 The effects of spinal cord Tregs on EAE mice. A, B
Tregs derived from spleen of CFA-treated ­Foxp3hCD2KI mice (Spleen Treg)
or brain or spinal cord of MOG-treated F­ oxp3hCD2KI mice (Brain Treg and
SC Treg, respectively) or only PBS were injected intravenously at day 17 inwild-type mice that were subjected to EAE. (PBS; N = 6, Spleen Treg; N = 6,
Brain Treg; N = 7, SC Treg; N = 6.) Clinical score of recipient mice (A). Spinal
cords of EAE mice at day 27 derived from (A) were stained with luxol fast
blue (LFB) & crecyl violet (CV), antibodies targeting MBP, Iba1 or GFAP.
Representative images were shown. Images were obtained by 20 objective. Scale bar; 100 µm. To assess the level of gliosis or accumulation of
myeloid cells, Iba1 or GFAP positive area was measured (B). P values were
determined by one-way ANOVA. The data are shown as the mean ± s.e.m.
Acknowledgements
We thank the Laboratory for Research Support, Medical Institute of Bioregulation (Kyushu University), for maintenance of the various research equipmentused in this study. This work was supported in part by the MEXT Cooperative
Research Project Program, Medical Research Center Initiative for High Depth
Omics, and CURE:JPMXP1323015486 for MIB, Kyushu University. We thankProfessor Mikita Suyama and Dr. Chie Kikutake for providing the environment
for NGS analysis.
Author contributions
M.W. and M.I conceived the study and designed the experiments. M.W., A.M.,
N.A., A.N., M.K. and Y.H. performed the experiments and analyzed the data.
M.W. and M.I. wrote the manuscript. All the authors edited the manuscript.
Funding
This work was funded by JSPS KAKENHI 21H02719, 21H00432, 21H05044,
21K19382, 22H05061 and 23H04785; MOON SHOT 21zf0127003h; AMEDPRIME 22gm6210012; AMED- 22wm0425011; JST-21470411; and a Research
grant from the Chemo-Sero-Therapeutic Research Institute, the Kishimoto
Family Foundation, the Uehara Memorial Foundation (M.I.).
Availability of data and materials
Bulk RNA-seq data for Tregs are available under accession number GSE252867.
Bulk RNA-seq data from the brain and spinal cord are available under accession number GSE252641. scRNA-seq data for Tregs are available under accession number GSE252368.

Declarations
Ethics approval and consent to partcipate
All animal care and experiment procedures were approved with a No. A22182-1 by the committee on the Ethics of Animal Experiments of Kyushu
University. All experiments were performed to keep animal pain, stress, andnumbers to a minimum.
Competing interests
The authors have declared that no conflict of interest exists. The authors
declare no competing financial interests.
Received: 11 February 2024 Accepted: 27 May 2024

Page 15 of 16

References
1. Fontenot JD, Gavin MA, Rudensky AY. Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. Nat Immunol.
2003;4(4):330–6.
2. Hori S, Nomura T, Sakaguchi S. Control of regulatory T cell developmentby the transcription factor Foxp3. Science. 2003;299(5609):1057–61.
3. Muñoz-Rojas AR, Mathis D. Tissue regulatory T cells: regulatory chameleons. Nat Rev Immunol. 2021;21(9):597–611.
4. Panduro M, Benoist C, Mathis D. Tissue tregs. Annu Rev Immunol.
2016;34:609–33.
5. Ito M, et al. Brain regulatory T cells suppress astrogliosis and potentiate
neurological recovery. Nature. 2019;565(7738):246–50.
6. Li C, et al. TCR transgenic mice reveal stepwise, multi-site acquisition of
the distinctive fat-treg phenotype. Cell. 2018;174(2):285-299.e12.
7. Delacher M, et al. Precursors for nonlymphoid-tissue treg cells reside insecondary lymphoid organs and are programmed by the transcription
factor BATF. Immunity. 2020;52(2):295-312.e11.
8. Delacher M, et al. Genome-wide DNA-methylation landscapedefines specialization of regulatory T cells in tissues. Nat Immunol.
2017;18(10):1160–72.
9. Delacher M, et al. Single-cell chromatin accessibility landscape
identifies tissue repair program in human regulatory T cells. Immunity.
2021;54(4):702-720.e17.
10. Yshii L, et al. Astrocyte-targeted gene delivery of interleukin 2 specificallyincreases brain-resident regulatory T cell numbers and protects against
pathological neuroinflammation. Nat Immunol. 2022;23(6):878–91.
11. O’Connor RA, Anderton SM. Foxp3+ regulatory T cells in the control of experimental CNS autoimmune disease. J Neuroimmunol.
2008;193(1–2):1–11.
12. Dombrowski Y, et al. Regulatory T cells promote myelin regeneration in
the central nervous system. Nat Neurosci. 2017;20(5):674–80.
13. Lahl K, et al. Selective depletion of Foxp3+ regulatory T cells induces a
scurfy-like disease. J Exp Med. 2007;204(1):57–63.
14. Sakai R, et al. Kidney GATA3+ regulatory T cells play roles in the convalescence stage after antibody-mediated renal injury. Cell Mol Immunol.
2021;18(5):1249–61.
15. Cao Z, et al. Role of Kruppel-like factors in leukocyte development, function, and disease. Blood. 2010;116(22):4404–14.
16. Kim KS, et al. Dietary antigens limit mucosal immunity by inducing regulatory T cells in the small intestine. Science. 2016;351(6275):858–63.
17. Mickael ME, Bhaumik S, Basu R. Retinoid-related orphan receptor RORγt
in CD4(+) T-cell-mediated intestinal homeostasis and inflammation. Am J
Pathol. 2020;190(10):1984–99.
18. Ramanan D, et al. Homeostatic, repertoire and transcriptional relationships between colon T regulatory cell subsets. Proc Natl Acad Sci USA.
2023;120(50): e2311566120.
19. Ramanan D, et al. Regulatory T cells in the face of the intestinal microbiota. Nat Rev Immunol. 2023;23(11):749–62.
20. McGeachy MJ, Stephens LA, Anderton SM. Natural recovery and protection from autoimmune encephalomyelitis: contribution of CD4+CD25+
regulatory cells within the central nervous system. J Immunol.
2005;175(5):3025–32.
21. Reynolds AD, et al. Neuroprotective activities of CD4+CD25+ regulatory T cells in an animal model of Parkinson’s disease. J Leukoc Biol.
2007;82(5):1083–94.
22. Thonhoff JR, et al. Expanded autologous regulatory T-lymphocyte
infusions in ALS: a phase I, first-in-human study. Neurol Neuroimmunol
Neuroinflamm. 2018;5(4): e465.
23. Beers DR, et al. ALS patients’ regulatory T lymphocytes are dysfunctional,
and correlate with disease progression rate and severity. JCI Insight.
2017;2(5): e89530.
24. Kalekar LA, et al. Regulatory T cells in skin are uniquely poised to suppress
profibrotic immune responses. Sci Immunol. 2019;4(39):eaaw2910.
25. Liston A, et al. Brain regulatory T cells. Nat Rev Immunol.
2024;25(5):326–37.
26. Miyao T, et al. Plasticity of Foxp3(+) T cells reflects promiscuous Foxp3
expression in conventional T cells but not reprogramming of regulatory T
cells. Immunity. 2012;36(2):262–75.
27. Sekiya T, et al. Nr4a receptors are essential for thymic regulatory T cell
development and immune homeostasis. Nat Immunol. 2013;14(3):230–7.

Watanabe et al. Journal of Neuroinflammation(2024) 21:146

28. Funato H, et al. Effects of a calcium antagonist, lacidipine, on experimental focal cerebral ischemia in rats. Jpn J Pharmacol. 1997;75(4):415–23.

Publisher’s NoteSpringer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Page 16 of 16