# Id2 levels determine the development of effector vs. exhausted tissue-resident memory CD8+ T cells during CNS chronic infection

Aboubacar Sidiki K Coulibaly, Lucie Nozeran, Céline Thomann, Marine Alis, Emilie Bassot, Ali Hassan, Rémi Porte, Marcy Belloy, Nicolas Blanchard, Frederick Masson

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## To cite this version:

Aboubacar Sidiki K Coulibaly, Lucie Nozeran, Céline Thomann, Marine Alis, Emilie Bassot, et al.  
Id2 levels determine the development of effector vs. exhausted tissue-resident memory CD8+ T cells  
during CNS chronic infection. Cell Reports, 2025, 44 (6), pp.115861. 10.1016/j.celrep.2025.115861.  
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**Cell Reports**

# Id2 levels determine the development of effector vs. exhausted tissue-resident memory CD8+ T cells during CNS chronic infection

## Graphical abstract

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## Authors

Aboubacar Sidiki K. Coulibaly,
Lucie Nozeran, Céline Thomann, ...,
Marcy Belloy, Nicolas Blanchard,
Frederick Masson

## Correspondence

frederick.masson@inserm.fr

## In brief

Coulibaly et al. found that the expression level of the transcriptional regulator Id2 dictates brain CD8 Trm functional states during chronic *Toxoplasma gondii* infection. Id2 deficiency reduces Trm effector functions and tissue-retention molecule expression and promotes Trm exhaustion, while its overexpression limits Trm exhaustion.

## Highlights

* Single-cell RNA-seq reveals heterogeneous Id2 levels in effector vs. exhausted brain CD8 Trms

* Id2 deficiency impairs tissue-retention molecules and promotes exhaustion in brain CD8 Trms

* Id2-E2A axis regulates early CD8 Trm development during the acute phase of *T. gondii* infection

* Id2 overexpression represses CD8 Trm exhaustion during chronic *T. gondii* infection

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Article

# Id2 levels determine the development of effector vs. exhausted tissue-resident memory CD8+ T cells during CNS chronic infection

Aboubacar Sidiki K. Coulibaly,<fnref n="1" /> Lucie Nozeran,<fnref n="1" /> Céline Thomann,<fnref n="1" />,<fnref n="2" /> Marine Alis,<fnref n="1" /> Emilie Bassot,<fnref n="1" /> Ali Hassan,<fnref n="1" /> Rémi Porte,<fnref n="1" /> Marcy Belloy,<fnref n="1" /> Nicolas Blanchard,<fnref n="1" /> and Frederick Masson<fnref n="1" />,<fnref n="3" />,*

## SUMMARY

Tissue-resident memory T cells (Trms) are essential for regional immunity in non-lymphoid tissues. Although single-cell transcriptomics have revealed Trm heterogeneity in various diseases, the molecular mechanisms behind this diversity are unclear. To investigate this, we performed single-cell transcriptomic analysis of brain CD8+ T cells from mice chronically infected with *Toxoplasma gondii*. This analysis revealed a heterogeneous expression of the transcriptional regulator Id2 in brain Trms, correlating with different functional states. Using mixed bone marrow chimeras, we found that Id2 deficiency in T cells caused parasite-specific Trms to develop an altered phenotype with diminished effector functions and reduced expression of the key tissue-retention molecules CD49a, CXCR6, and CD103. Furthermore, Id2 loss in brain-infiltrating CD8+ T cells led to the accumulation of exhausted PD1+Tox+CD8+ Trm cells, while Id2 overexpression repressed T cell exhaustion. Overall, our study shows that Id2 levels dictate the acquisition of effector vs. exhausted phenotypes in CD8+ Trms during chronic CNS infection.

## INTRODUCTION

In recent years, tissue-resident memory T cells (Trms) have been identified as a crucial T cell population stably residing within non-lymphoid tissues and playing an essential role to protect against pathogen reinfections.<fnref n="1" />,<fnref n="2" /> Initially recognized for their protective role against reexposure to acute infections, Trm cells have also been found to exert important functions in situations of antigenic persistence.<fnref n="3" /> Indeed, these Trm-like cells play a protective role against chronic latent pathogen infection,⁴ and their presence has been correlated with good prognosis in solid cancers.⁵ Besides these protective functions, Trms can also play a deleterious role during chronic inflammatory and autoimmune diseases such as psoriasis, type 1 diabetes, or central nervous system (CNS) autoimmune diseases.⁶⁻⁸

Trm retention in non-lymphoid organs depends on the establishment of a tissue residency transcriptional program orchestrated by key transcriptional regulators, including Blimp-1 and its homolog Hobit, as well as Runx3 and Bhlhe40.<fnref n="2" /> The implementation of this tissue residency program results in the induction of tissue-retention-associated molecules such as CD69, CXCR6, CD49a, and CD103, along with the downregulation of tissue egress signals mediated by S1PR1 and KLF2 and a tissue-specific metabolic adaptation to the target tissue.<fnref n="2" /> Importantly, recent transcriptomic analyses have revealed the phenotypic and functional heterogeneity of Trms in various

pathophysiological contexts.⁴,⁹⁻¹⁴ Indeed, Trm subsets with distinct transcriptional signatures have been shown to coexist within a given tissue, including “effector-like” Trms with increased effector potential, exhausted Trms exhibiting classical phenotypical features of T cell exhaustion, and “stem-like” Trms potentially capable of self-replenishment.⁴,⁹,¹⁰ The heterogeneity of Trms is likely influenced by variations in cytokine signaling, the extent of CD4+ T cell help, and a differential access to specific antigens. However, the molecular mechanisms driving such phenotypical and functional diversity are still poorly understood.

In CD8+ T cells, these signals are typically integrated at the transcriptional level by a handful of key transcriptional regulators. Recent studies have shown that transcription factors important for effector CD8+ T cell differentiation, such as T-bet, Blimp-1, or Runx3, also played an important role in regulating the development of Trms, highlighting the intricate link between the effector and the Trm transcriptional programs of CD8+ T cell differentiation.¹⁵⁻²¹ We and others have previously demonstrated that the lineage-fate decision into effector or memory CD8+ T cells during an acute and cleared pathogen infection is regulated by the interplay between the Inhibitor of DNA binding 2 (Id2) transcriptional regulator and the class I basic-helix-loop-helix protein (bHLH) family of transcription factors called E proteins, including E2A, HEB, and E2-2.²²⁻²⁵ Id2 is upregulated in effector CD8+ T cells during an acute viral

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<footnote n="1">¹Toulouse Institute for Infectious and Inflammatory Diseases (Infinity), INSERM, CNRS, University of Toulouse, 31024 Toulouse, France</footnote>

<footnote n="2">²Present address: 3d.FAB, CNRS, INSA, CPE-Lyon, UMR5246, ICBMS, University Claude Bernard Lyon 1, Villeurbanne, France</footnote>

<footnote n="3">³Lead contact</footnote>

<footnote>*Correspondence: frederick.masson@inserm.fr</footnote>

<footnote>https://doi.org/10.1016/j CELREP.2025.115861</footnote>
infection, and its loss cripples effector differentiation and pro-
grams CD8+ T cells to adopt a memory fate through the E2A-
mediated activation of Tcf7 (encoding Tcf1).<sup>23,24</sup> While the
functions of E2A and its inhibitor Id2 have been investigated
during acute viral infection, much less is known about the
role of this transcriptional axis in CD8+ Trm cells responding
to a tissue-restricted chronic infection. Id2 has been shown
to contribute to the homeostasis of intestinal Trm/intraepithelial
lymphocytes (IELs) after an acute and resolved lymphocytic
choriomeningitis virus (LCMV) infection, and accordingly, Id2
full knockout (KO) mice lack IELs.<sup>10,26</sup> Whether and how Id2
plays a role in Trm biology in other peripheral tissues is un-
known. The role of Id2 in T cell exhaustion is also still debated,
as its expression is increased in terminally exhausted cells dur-
ing LCMV chronic infection and in terminally exhausted tumor-
infiltrating lymphocytes (TILs).<sup>27,28</sup> On the other hand, during
chronic LCMV infection, Id2 deficiency promotes the differenti-
ation of CD8+ T cells that show features of progenitors of ex-
hausted T cells (Tpex cells) with increased Tcf1 expression.<sup>29</sup>
Finally, Tox, the master regulator of the transcriptional and
epigenetic remodeling of T cell exhaustion,<sup>27,30,31</sup> has been
shown to repress Id2 in a model of CNS autoimmunity,<sup>32</sup> and
accordingly, Tox-forced expression decreased Id2 expression
in Tpex cells.<sup>27</sup> Collectively, these studies suggest a potential
role of Id2 in regulating Trm biology and T cell exhaustion. In
this study, we have explored the role of Id2 and its interplay
with E2A in controlling Trm fate in a model of chronic Toxo-
plasma gondii (T. gondii) infection that establishes a latent
infection in the CNS. Our data showed that Id2 is expressed
in Trms and that it repressed their acquisition of an exhaus-
tion-associated phenotype while promoting the expression of
effector functions and tissue-retention molecules.

RESULTS

Id2 expression level correlates with the effector
potential of brain CD8+ Trms during chronic T. gondii
infection

To understand the role of Id2 in Trm biology during chronic *T. gondii* infection, we first wished to determine its expression pattern in CD8⁺ T cells responding to *T. gondii* infection. To this end, we performed a single-cell transcriptomic analysis (single-cell RNA sequencing; scRNA-seq) of CD8⁺ T cells isolated from the brain and the spleen of mice chronically infected with *Toxoplasma gondii*.GRA6-OVA (Tg.GRA6-OVA)³³ (Figure 1A). We have recently shown using this infection model that, following the acute phase of infection, *T. gondii* establishes a latent infection in the brain (from day 21 post-infection onward) that is efficiently controlled by parasite-specific brain CD8⁺ Trms.⁴ Unsupervised clustering analysis uncovered six CD8⁺ T cell clusters in the brain (cluster [cl]2, cl3, cl6, cl7, cl8, and cl9) and four clusters in the spleen (cl0, cl1, cl4, and cl5) (Figure 1B). Notably, cl2, cl3, cl6, and cl7 had low expression of the tissue-egress-associated molecules *Klf2* and *S1pr1*, while they expressed various levels of Trm-associated markers, among which were *Cd69*, *Cxcr6*, *Itga1* (encoding CD49a), and *Itgae* (encoding CD103), suggestive of a Trm phenotype (Figure 1C). In line with this, gene set enrichment analysis

(GSEA) showed an enrichment of previously published core
Trm and brain Trm gene signatures¹⁰,³⁴ in cells from cl2, cl3,
cl6, and cl7 (Figure 1D). Aside from these four Trm clusters,
which accounted for more than 94% of the brain-infiltrating
CD8⁺ T cells, we identified a small central memory T cell (Tcm)
cluster, characterized by high Tcf7 expression within the brain
(cl8), and a cluster of terminal effector cells marked by high
Klrg1 expression (cl9), which was also found in the spleen (cl5)
(Figure 1C). Notably, Id2 was expressed in all brain Trm clusters,
although its expression was heterogeneous, with the highest
expression observed in cl2 (Figure 1C). Indeed, of the two
most abundant Trm clusters, cl2 (42% of brain-infiltrating CD8⁺
T cells) and cl3 (39% of brain-infiltrating CD8⁺ T cells), we found
that the expression of Id2 was significantly higher in cl2
compared with cl3 (Figure 1E). Id2 was also highly expressed
within terminal effector T cell clusters from the brain (cl9) and
spleen (cl5), as expected from previous studies.²³,²⁴ Since Id2
was differentially expressed (DE) between the two most abun-
dant Trm clusters, cl2 and cl3 (Figure 1E), we asked whether
this difference of expression may directly impact their transcrip-
tome. GSEA comparison between cl2 and cl3 showed an enrich-
ment of a previously published Id2-induced gene signature²⁴ in
cl2 and its depletion in cl3. Conversely, an Id2-repressed gene
signature was positively enriched in cl3 and depleted in cl2, sug-
gesting a direct impact of Id2 expression level in regulating the
transcriptome of these Trm clusters (Figure 1F).

Given the fact that Id2 expression has been previously shown to correlate with effector CD8+ T cell differentiation, we then wondered whether the heterogeneity of Id2 expression in Trm clusters could correlate with differential functionality. Accordingly, CD8+ T cells from cl2 displayed high expression of genes coding for effector molecules (Ifng, Tnf, and Gzmb), high expression of the tissue-retention-associated genes Itga1 (encoding the integrin CD49a) and Itgae (encoding the integrin CD103) and the chemokine receptor Cxcr6, and low expression of exhaustion-associated genes (Tox and Pdcd1). Conversely, cells from cl3 exhibited a low level of effector molecules (Ifng, Tnf, and Gzmb) combined with an “exhaustion” phenotype characterized by high expression of genes associated with exhaustion, such as the transcription factors Tox and Eomes and the inhibitory receptors Pdcd1 and Tigit, as well as a lower expression of the tissue-retention-associated genes Itgae and Itga1 (Figure 1G). In line with this, when comparing the genes DE between cl2 and cl3, we found that mainly genes involved in effector functions (Ifng, Tnf, Gzma, Gzmb, and Fasl) and Trm differentiation (Bhlhe40, Zfp36, Itgae, Itga1, and Cxcr6) were upregulated in cl2, whereas the genes downregulated in cl2 compared with cl3 were instead linked with T cell exhaustion (Tox, Eomes, Batf, Lag3, Pdcd1, Tigit, and Slamf6) (Figure S1A). Consistent with the scRNA-seq data, our flow cytometry analysis confirmed the functional exhaustion of PD1⁺Tox⁺CD69⁺ Trm cells, which showed a decreased proportion of total granzyme B⁺ cells, total interferon-γ (IFN-γ)⁺ cells, and IFN-γ⁺/granzyme B⁺ double producers (Figure S1B). Of note, the smaller Trm clusters cl6 and cl7 also expressed Tox but, in contrast to cl3, still showed high effector gene expression (Ifng and Gzmb), suggesting that they may represent an intermediate stage of T cell exhaustion as previously reported.³⁵
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<figure><img src="image_14.png" /><figcaption>Figure 1. Heterogeneity of Id2 expression across brain Trm subsets correlates with their functional heterogeneity during the chronic phase of *T. gondii* infection</figcaption></figure>

(A) scRNA-seq of CD8+ T cells isolated from the brain and the spleen of mice infected with Tg.GRA6-OVA at day 154 post-immunization. Uniform Manifold Approximation and Projection (UMAP) shows segregation between spleen and brain CD8+ T cells.

(B) UMAP of SEURAT-generated clusters (left) and cluster frequencies (right).

(C) Dot plot of gene expression for the indicated genes involved in CD8+ T cell differentiation and tissue residency.

(D) GSEA for the indicated published gene signatures. Normalized enrichment score (NES) and adjusted *p* values are shown.

(E) Violin plot shows Id2 expression in the two most abundant Trm clusters, cluster 2 and cluster 3. Statistical differences were assessed using Wilcoxon rank-sum test.

(F) GSEA of DE genes decreased in Id2-deficient CD8+ T cells (Id2-induced gene signature) or increased in Id2-deficient CD8+ T cells (Id2-repressed gene signature) from Masson et al.²⁴ in cluster 2 vs. cluster 3.

(G) Dot plot of gene expression for the indicated genes involved in CD8+ T cell exhaustion and effector functions.

Finally, we asked whether Id2-induced gene signature was also enriched in brain Trms found in other physiopathological contexts, such as CNS autoimmunity, in which the autoantigen is continuously expressed akin to chronic *T. gondii* infection. To

this end, we reanalyzed scRNA-seq data from a previously published model of autoimmune neuron targeting disease, in which autoreactive CD8+ Trm cells residing in the hypothalamus are involved in the progressive loss of neurons over time.¹¹ This
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(legend on next page)
analysis showed a significant enrichment of the Id2-induced gene signature in autoreactive Trms from the hypothalamus compared with their circulating splenic counterparts (Figure S1C). In addition, we found that the gene signature of these autoreactive brain Trms was also very significantly enriched in cl2 from *T. gondii*-infected mice, indicating a high similarity between the transcriptional signatures of the Trms found in this model of CNS autoimmune disease and of brain Trms from *T. gondii* chronically infected mice (Figure S1D). Finally, we evaluated whether these findings could be extended to a human CNS autoimmune disease such as multiple sclerosis (MS). To this end, we assessed the enrichment in the Id2 high (cl2) and Id2 low (cl3) Trm clusters from *T. gondii*-infected mice of the recently described gene signature of Trm-like cells ITGA1⁺ (encoding CD49A) from the cerebrospinal fluid (CSF) of MS patients extracted from a meta-analysis of multiple scRNA-seq of CSF cells from MS patients.¹² Importantly, these CSF-derived Trm-like cells were reported to express a high level of Id2.¹² Remarkably, the gene signature of the ITGA1⁺ Trms was highly enriched in the “Id2high” cl2 (normalized enrichment score [NES] = 1.1421, nominal *p* < 0.001) and poorly enriched in the “Id2low” cl3 (NES = 1.104, nominal *p* = 0.28) (Figure S1E).

Collectively, our results indicate that Id2 expression level correlates with the functional state of brain CD8⁺ Trms during CNS chronic infection and that Id2-controlled genes are enriched in brain Trms across CNS infection and CNS autoimmunity.

## Id2 deficiency leads to the formation of brain Trms with an altered phenotype during chronic CNS infection

We then endeavored to test whether Id2 expression level actively regulates brain Trm development and function during chronic CNS *T. gondii* infection. To this end, we generated mixed bone marrow (BM) chimeras by reconstituting lethally irradiated F1 CD45.1⁺, CD45.2⁺ wild-type (WT) mice with a mix of BM cells

from T-cell-specific Id2-deficient Id2fl/fl CD4Cre⁺ mice (Id2 TKO, CD45.2⁺) and BM from CD45.1⁺ WT congenic mice that were left to reconstitute 7–8 weeks before *T. gondii* infection. As additional controls for the genetic background of the Id2floxed;CD4cre mouse colony, mixed BM chimeras reconstituted with the BM from WT Id2floxed;CD4cre littermates (noted as WT CD45.2⁺ hereafter) and from WT CD45.1⁺ mice were generated. Due to an increased sensitivity of the BM chimeras during the acute phase of the infection with Tg.GRA6-OVA, mice were infected with an attenuated *T. gondii* strain expressing the model antigen GRA6-OVA (Tg.ΔGRA2.GRA6-OVA), which establishes a normal latency in the brain during the chronic phase³⁶ (Figure 2A). As previously reported, during acute pathogen infections,²² Id2 deficiency in T cells strongly decreased the accumulation of pathogen-specific (KᵇOVA-dex-tramer [Dex]⁺) CD8⁺ T cells in both brain and spleen as well as the formation of KLRG1⁺ short-lived effector CD8⁺ T cells, and the loss of Id2-deficient (CD45.2⁺) OVA-specific CD8⁺ T cells was accentuated in the chronic phase (9–11 weeks post-infection) compared with the acute phase (2 weeks post-infection) of the infection (Figures 2B and S2A–S2C). Moreover, the parasite load in the brain of the Id2 TKO:WT mixed BM chimeras was significantly higher than in the WT:WT control chimeras, demonstrating that the loss of Id2 in about half of total CD8⁺ and CD4⁺ T cells had a significant impact on the parasite control (Figure S2D).

We then investigated the phenotype of OVA-specific CD8⁺ T cells during the chronic phase of *T. gondii* infection and, in particular, the acquisition of the Trm phenotype characterized by expression of key molecules involved in the retention of Trms within the tissue, such as CD69, CD49a, CXCR6, and CD103. Brain-infiltrating OVA-specific CD8⁺ T cells from both the Id2-deficient (CD45.2⁺) and the WT (CD45.1⁺) CD8⁺ T cell compartments of the mixed BM chimeras largely expressed the Trm marker CD69, in contrast to their splenic counterparts,

## Figure 2. Loss of Id2 alters the differentiation of parasite-specific brain Trms during chronic *T. gondii* infection

(A) Experimental workflow of mixed bone marrow (BM) chimeras reconstituted with a mix of WT (CD45.1⁺) and Id2 TKO (CD45.2⁺) BM at a ratio of 1:4 and infected with Tg.ΔGRA2.GRA6-OVA. Mice were analyzed 9–11 weeks post-infection (p.i.).

(B) Representative contour plots (left) and graph (right) show the frequency of Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) OVA-specific (Kᵇ-OVA Dex⁺) CD8⁺ T cells within the brain.

(C) Representative contour plots show CD69 expression within Kᵇ-OVA Dex⁺CD8⁺ T cells of the indicated genotype from brain and spleen. Graph shows the percentage of CD69⁺ cells among brain WT (CD45.1⁺) and Id2 TKO (CD45.2⁺) OVA-specific CD8⁺ T cells.

(D) Representative contour plots of CD49a and CD103 expression among brain Id2 TKO (CD45.2⁺) or WT (CD45.1⁺) CD69⁺ Kᵇ-OVA Dex⁺CD8⁺ T cells during chronic phase (9–11 weeks p.i.).

(E) Bar graph shows the frequency of the indicated population among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) CD69⁺ Kᵇ-OVA Dex⁺CD8⁺ T cells (left) or total CD8⁺CD44⁺CD69⁺ T cells (right).

(F) Representative contour plots of CD49a and CXCR6 expression among brain Id2 TKO (CD45.2⁺) or WT (CD45.1⁺) CD69⁺ Kb-OVA Dex⁺CD8⁺ T cells during chronic phase (9–11 weeks p.i.).

(G) Bar graph shows the frequency of the indicated population among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) CD69⁺ Kb-OVA Dex⁺CD8⁺ T cells (left) or total CD8⁺CD44⁺CD69⁺ T cells (right).

(H) Representative contour plots show the intracellular expression of IFN-γ and granzyme B within brain Id2 TKO and WT on CD44⁺CD8⁺CD69⁺ T cells after restimulation with phorbol 12-myristate 13-acetate (PMA) and ionomycin in the presence of monensin.

(I) Bar graphs show the frequency of IFN-γ- (top) and granzyme B- (bottom) expressing cells after PMA/ionomycin restimulation among total Id2 TKO or WT CD69⁺CD8⁺T cells.

Data are pooled from two or three (E, G, and I), four (C), or five (B) independent experiments. Bars show the mean ± SEM. Statistically significant differences were determined using Wilcoxon matched-pairs signed rank test (B and I [bottom CD103⁻CD49a⁺ sample group]), paired t test (C and I [top and bottom CD103⁺CD49a⁺ sample group]), or multiple Wilcoxon matched-pairs signed rank test (E and G [right]) or multiple paired t test (G [left]) corrected for multiple comparisons using two-stage step-up method of Benjamini, Krieger, and Yekutieli. *p* < 0.05, **p** < 0.01, ***p** < 0.001, and ****p** < 0.0001. ns, not significant. Each dot represents an individual mouse.
A

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B

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C

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D

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E

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F

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G

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H

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I

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and the loss of Id2 had no impact on the proportion of CD69-expressing cells compared with WT cells (Figure 2C). Furthermore, WT CD69⁺ OVA-specific CD8⁺ T cells uniformly expressed CD49a and CXCR6, and around half (48.6% ± 4.0%) of CD49a⁺ cells also expressed CD103 (Figures 2D and 2F). Remarkably, compared with WT CD8⁺ T cells, Id2 deficiency led to the emergence of brain-infiltrating CD69⁺CD8⁺ T cells expressing neither of these key retention molecules in both OVA-specific and total CD44⁺CD69⁺CD8⁺ T cells, which was paralleled by a reciprocal decreased proportion of CD49a⁺ and CXCR6⁺ cells expressing or not CD103 (Figures 2D–2G). By contrast, control chimeras did not show any difference in Trm marker expression between the CD45.2⁺ and the CD45.1⁺ OVA-specific CD8⁺ T cell compartments (Figures S2E–S2G).

Our single-cell transcriptomic data suggested that high Id2 expression correlated with increased Trm effector functions, while lower Id2 expression was linked to a dysfunctional state. Thus, we next assessed the consequences of Id2 deficiency on effector molecule expression by brain CD8⁺ Trm cells. This analysis revealed that Id2 deficiency resulted in a marked decrease of IFN-γ expression by double-positive (CD69⁺CD49a⁺CD103⁻) and triple-positive (CD69⁺CD49a⁺CD103⁺) Trm and in a significant reduction of granzyme B expression by the triple-positive (CD69⁺CD49a⁺CD103⁺) Trm subset (Figures 2H and 2I). By contrast, no difference in effector functions was found in control chimeras between the CD45.2⁺ and the CD45.1⁺ WT brain CD8⁺ T cell compartments (Figure S2H).

At last, we investigated whether Id2 deficiency had a similar impact on CD4⁺ Trm cells. Id2 deficiency led to a decreased proportion of activated (CD44⁺) CD4⁺ T cells in both spleen and brain of *T. gondii*-infected mice during the chronic phase (Figure S3A). Similar to CD8⁺ T cells, lack of Id2 led to a decreased proportion of CD49a⁺⁻ and CXCR6⁺⁻-expressing cells among CD69⁺(CD44⁺)CD4⁺ Trm cells (Figures S3B–S3F).

Altogether, our results show that Id2 deficiency leads to the emergence of Trms exhibiting an altered phenotype characterized by decreased expression of tissue-retention molecules and reduced effector functions during the chronic phase of *T. gondii* infection.

## The Id2-E2A axis regulates the emergence of CD49a⁺CXCR6⁺ effector brain Trms

We reasoned that the decreased frequency of CD49a⁺ effector Trms upon Id2 deficiency could either reflect a loss of this population over time or, instead, suggest that Id2 played a role in the differentiation of this Trm subset. To resolve this issue, we analyzed the early development of Trms during the acute phase of the infection, i.e., 2 weeks after Tg.ΔGRA2.GRA6-OVA inoculation. At this early time point, a similar proportion of WT and Id2-deficient OVA-specific CD8⁺ T cells expressed CD69 (Figure 3A). Importantly, akin to the chronic phase, we observed a decreased frequency of CD49a-expressing cells and the reciprocal increase in double-negative cells upon Id2 deficiency among both total CD44⁺CD69⁺CD8⁺ T cells and OVA-specific CD69⁺CD8⁺ T cells (Figures 3B and 3C). As expected, CD103 was only weakly expressed at this early stage of the infection (Figure 3C). Moreover, granzyme B expression was downregulated in Id2-deficient total CD8⁺CD69⁺ Trm cells during the acute phase of the infection, albeit to a lower extent compared with the chronic phase (Figure 3D). Taken together, these results suggested that Id2 loss cripples the differentiation of effector Trm subtypes rather than impeding their maintenance.

Since Id2 has been reported to act in a dose-dependent manner during peripheral CD8⁺ T cell differentiation in response to an acute viral infection,²⁴ we next investigated whether increasing Id2 dosage could enhance the accumulation of OVA-specific CD8⁺ T cells and the generation of brain Trm cells expressing CD49a during Tg.GRA6-OVA infection. To address

<caption>**Figure 3.** The transcriptional axis Id2-E2A regulates the early differentiation of CD49a⁺CXCR6⁺ brain Trms during the acute phase of *T. gondii* infection</caption>

(A–D) Mixed BM chimeras Id2 TKO (CD45.2⁺):WT (CD45.1⁺) were generated as described in Figure 2A and were analyzed during the acute phase (2 weeks p.i.) of Tg.ΔGRA2.GRA6-OVA infection. (A) Representative contour plot (left) and graph (right) show the frequency of CD69⁺ cells among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) Kᵇ-OVA Dex⁺CD8⁺ T cells. (B) Representative contour plot (left) and graph (right) show the frequency of CD49a⁺ cells among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) Kᵇ-OVA Dex⁺CD69⁺CD8⁺ T cells. (C) Bar graph shows the percentage of the indicated CD8⁺ T cell population among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) Kᵇ-OVA Dex⁺CD69⁺CD8⁺ T cells (left) or total CD8⁺CD44⁺CD69⁺ T cells (right). (D) Representative contour plots (left) show granzyme B expression among brain Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) total CD44⁺CD8⁺T cells and graph (right) shows the frequency of granzyme-B-expressing cells among brain Id2 TKO and WT CD69⁺CD44⁺CD8⁺ T cells.

(E and F) Adoptive transfer of T cell receptor (TCR) transgenic OVA-specific CD8⁺ T cells (OT-I) transduced with retroviruses encoding Id2 (Id2 OE) or a control (Ctr) empty vector and GFP as a fluorescent reporter to recipient mice subsequently infected with Tg.GRA6-OVA. Mice were analyzed at day 14 p.i. and brains were collected. (E) Representative contour plots (left) and bar graph (right) show the percentage of CD69⁺ cells among brain Ctr and Id2 OE OT-I GFP⁺ (CD45.1⁺). (F) Representative contour plots (top) show the expression of CD103 vs. CD49a in brain Ctr and Id2 OE CD69⁺OT-I GFP⁺ (CD45.1⁺) CD8⁺T cells. Bar graph (bottom) shows the percentage of the indicated population within brain Ctr and Id2 OE CD69⁺OT-I GFP⁺ (CD45.1⁺) cells.

(G–I) Adoptive transfer of TCR transgenic OVA-specific CD8⁺ T cells (OT-I) transduced with retroviruses encoding the E2A isoform E47 (E2A OE) or a control (Ctr) empty vector and mCherry as a fluorescent reporter to recipient mice subsequently infected with Tg.GRA6-OVA. Mice were analyzed at day 14 p.i. and brains were collected. (G) Representative contour plots (left) and bar graph (right) show the percentage of brain CD69⁺ cells among Ctr and E2A OE OT-I mCherry⁺ (CD45.1⁺) cells. (H) Representative contour plots (left) show the expression of CD103 vs. CD49a in Ctr and E2A OE in brain CD69⁺OT-I mCherry⁺ (CD45.1⁺) CD8⁺T cells. Bar graph (right) shows the percentage of the indicated population within Ctr and E2A OE CD69⁺OT-I mCherry⁺ (CD45.1⁺) cells from the brain. (I) Representative contour plots (left) show the expression of CXCR6 vs. CD49a in Ctr and E2A OE brain CD69⁺OT-I mCherry⁺ (CD45.1⁺) CD8⁺T cells. Bar graph (right) shows the percentage of the indicated population within Ctr and E2A OE CD69⁺OT-I mCherry⁺ (CD45.1⁺) cells from the brain.

Data are pooled from two (D, G, H, and I) or three (A, B, C, E, and F) independent experiments. Bars show the mean ± SEM. Statistically significant differences were determined using paired t test (A, B, and D); multiple Wilcoxon matched-pairs signed rank test (C, left) or multiple paired t test (C, right) corrected for multiple comparisons using two-stage step-up method of Benjamini, Krieger, and Yekutieli; unpaired t test (E and G); multiple unpaired t test with Welsh correction (H); or multiple Mann-Whitney tests (F and I) corrected for multiple comparisons using two-stage step-up method of Benjamini, Krieger, and Yekutieli. \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, and \*\*\*\*p < 0.0001. ns, not significant. Each dot represents an individual mouse.
this point, OVA-specific OT-I CD8+ T cells were transduced with a retroviral vector encoding Id2 and GFP as reporter or with a control-IRES-GFP vector and were transferred into recipient mice that were infected with Tg.GRA6-OVA 1 day later (Figure S4A). Remarkably, Id2 overexpression (OE) strongly increased the total number of OT-I cells in both brain and spleen (Figures S4B and S4C). Moreover, the frequency of CD49a+ expressing cells among CD69+ OT-I Trms increased upon Id2 OE (Figures 3E and 3F).

Next, we explored the molecular mechanisms underpinning this increased formation of CD49a+ Trm cells upon Id2 OE. As the expression of the transcriptional regulator Hobit has been reported to correlate with the expression of CD49a in Trms,³⁷ we hypothesized that Id2 may promote the generation of CD49a+ Trms through the induction of Hobit expression. To address this question, we made use of OT-I cells crossed with the Hobit-TdTomato-Cre-DTR reporter mouse³⁸ to test the effect of Id2 OE on Hobit expression in developing brain OT-I Trms during the acute phase of *T. gondii*-OVA infection. Our data showed that the expression level of Hobit-TdTomato in various CD69+ Trm subsets (CD49a⁻CD103⁻, CD49a⁺CD103⁻, and CD49a⁺CD103⁺) was not impacted by Id2 OE, indicating that Id2 OE does not increase the formation of CD49a-expressing Trms through an increase in Hobit expression (Figures S4D and S4E).

Id2 has been previously shown to repress memory precursor formation through the inhibition of E2A transcriptional activity during acute pathogen infection.²⁴ Moreover, our scRNA-seq data showed that *Tcf3* (which encodes E2A) was the only E-protein-coding gene expressed in the brain Trm clusters, in contrast to *Tcf12* (encoding HEB) and *Tcf4* (encoding E2-2) (Figure S4F). To determine whether Id2 could act through the inhibition of E2A activity during Trm development, we asked whether E2A OE could phenocopy the impact of Id2 deficiency on the Trm phenotype. Two weeks post-infection, the total number and frequency of OT-I cells overexpressing E2A were drastically decreased compared with control OT-I cells both in brain and in spleen (Figure S4G). Phenotypically, E2A OE did not impact the proportion of CD69-expressing OT-I cells infiltrating the brain, but it led to a significantly decreased proportion of CD69+ OT-I cells expressing CD49a and CXCR6 compared with OT-I transduced with the control vector, similar to the effects observed upon Id2 deficiency (Figures 3H and 3I). Overall these results suggest that Id2 has an impact on the differentiation of CD49a⁺CXCR6⁺ Trm cells, potentially through the inhibition of the transcriptional activity of E2A.

Next, we asked whether Id2 controlled the expression of Trm retention molecules before the entry of CD8+ T cells into the brain. For this, we explored the expression of CD49a and CXCR6 on total effector CD44⁺CD8⁺ T cells from the spleen during the acute phase of the infection. Although CXCR6 and CD49a are suboptimally expressed in splenic activated (CD44⁺) CD8⁺ T cells during the acute phase of the infection, we observed a decreased proportion of CXCR6⁻ and CD49-expressing cells upon Id2 deficiency (Figure S4H). As some of these changes could be the results of a selective loss of CXCR6/CD49a-expressing cells during the course of the infection, we assessed the consequence of E2A OE in

*in vitro*-activated CD8+ T cells cultured in Trm polarizing conditions. Although our culture condition failed to induce CD49a in both control and E2A OE CD8+ T cells, we observed that E2A OE led to a significant decrease in CXCR6 expression compared with CD8+ T cells transduced with a control vector (Figure S4I). Taken together, these results indicate that the transcriptional axis Id2-E2A plays an important role in controlling the induction of Trm tissue-retention molecules.

## Id2 deficiency promotes brain Trm exhaustion during chronic *T. gondii* infection

Our transcriptomic data of CD8+ T cells isolated from the brain of chronically *T. gondii*-infected mice showed that the cluster of Trms exhibiting a lower Id2 expression (cl3) displayed a profile of T cell exhaustion characterized by high *Tox* and *Pdcd1* expression (see Figure 1G). These observations led us to hypothesize that the downregulation of Id2 expression might promote Trm exhaustion during chronic pathogen infection. To address this issue, we analyzed the exhaustion phenotype of CD8+ T cells isolated from the brain of Id2 TKO (CD45.2⁺):WT (CD45.1⁺) mixed BM chimeras and WT (CD45.2⁺):WT (CD45.1⁺) control chimeras during the acute and chronic phases of the infection. In line with former observations in the *T. gondii* infection model,⁴,³⁹ neither brain-infiltrating WT nor Id2-deficient parasite-specific (KᵇOVA Dex⁺)-specific CD69⁺CD8⁺ T cells exhibited any sign of exhaustion during the chronic stage of the infection, as shown by their lack of PD-1 and Tox expression (Figures 4A and 4B). Instead, cells coexpressing PD-1 and Tox were found among KᵇOVA-Dex-negative brain-infiltrating CD69⁺ CD8⁺ T cells (Figures 4A and 4B). This population of CD8+ T cells developed specifically during the chronic stage of the infection as indicated by the absence of PD-1 and Tox expression during the acute phase of the infection (Figure 4B). Moreover, this absence of exhaustion was not restricted to KᵇOVA-specific CD8⁺ T cells, as CD8+ T cells specific for another parasite antigen, Kᵇ-Tgd057/SVL8-specific CD8+ T cells,⁴⁰ did not show any expression of PD1 and Tox (Figures S5A and S5B). Remarkably, the proportion of cells expressing Tox and PD-1 among KᵇOVA-Dex-negative CD8⁺ T cells significantly increased among Id2-deficient CD8⁺ T cells compared with WT CD45.1⁺CD8⁺ T cells from Id2 TKO:WT mixed chimeras, while no differences were found between WT CD45.2⁺ and WT CD45.1⁺CD8⁺ T cells in control chimeras (Figures 4A, 4B, S5C, and S5D). PD1⁺Tox⁺ cells were largely restricted to cells double negative for CD49 and CD103 in the WT CD8⁺CD69⁺ T cell compartment (Figures 4C and S5D). By contrast, Id2 deficiency led to an increased proportion of PD-1⁺Tox⁺ cells across all Trm subsets (Figure 4C). Functionally Id2 deficiency decreased granzyme B expression in PD1⁺Tox⁺CD69⁺ cells compared with WT cells but did not significantly impact IFN-γ expression (Figure 4D).

*Tox* has been previously reported to repress Id2 expression and Id2-dependent gene signature in encephalitogenic T cells in a model of autoimmune encephalitis.³² Since Id2 is important to repress E2A-mediated activation of *Tcf7* (encoding *Tcf1*) expression during an acute viral infection²⁴ and *Tcf1* is required for the generation of *Tpex* cells during chronic infection, we then
<figure><img src="image_35.png" /></figure>

<figure><img src="image_36.png" /><figcaption>**Figure 4.** Id2 deficiency leads to increased proportion of exhausted CD8⁺ T cells in the brain of mice chronically infected with *T. gondii*</figcaption></figure>

Mixed BM chimeras Id2 TKO (CD45.2⁺):WT (CD45.1⁺) were generated as described in Figure 2A and were analyzed during the acute phase (2 weeks p.i.) and the chronic phase (9–11 weeks p.i.) of Tg.ΔGRA2.GRA6-OVA infection.

(A) Gating strategy and representative contour plots of PD-1 and Tox expression in WT (CD45.1⁺) and Id2 TKO (CD45.2⁺) Kᵇ-OVA Dex-negative CD8⁺CD44⁺CD69⁺ T cells (top) and Kᵇ-OVA Dex⁺CD8⁺CD69⁺ T cells (bottom) from the brain during the chronic phase of the infection.

(B) Bar graph shows the frequency of PD-1⁺TOX⁺-expressing cells either among WT (CD45.1⁺) and Id2 TKO (CD45.2⁺) Kᵇ-OVA Dex⁺CD69⁺CD8⁺T cells or among Kᵇ-OVA Dex-negative CD8⁺CD44⁺CD69⁺T cells from the brain during the acute and chronic stages of the infection.

(C) Bar graph shows the percentage of PD-1⁺TOX⁺-expressing cells within the indicated population among brain WT (CD45.1⁺) and Id2 TKO (CD45.2⁺) Kᵇ-OVA Dex-negative CD69⁺CD44⁺CD8⁺T cells during the chronic phase of the infection.

(D) Graphs show the frequency of granzyme B- and IFN-γ-expressing cells after PMA/ionomycin restimulation among WT or Id2 TKO PD1⁺Tox⁺CD69⁺ Kb-OVA Dex-negative CD8⁺T cells.

(E) Representative dot plots and graph show the proportion of Slamf6⁺Tim3⁻ among Id2 TKO (CD45.2⁺) and WT (CD45.1⁺) PD-1⁺Tox⁺CD69⁺CD44⁺CD8⁺T cells. Data are from one experiment (D) or pooled from two (E) and six (B and C) independent experiments. Bars show the mean ± SEM. Statistically significant differences were determined using paired t test (D), Wilcoxon matched-pairs signed rank test (B and E), and multiple Wilcoxon matched-pairs signed rank test corrected for multiple comparisons using two-stage step-up method of Benjamini, Krieger, and Yekutieli (C). \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, and \*\*\*\*p < 0.0001. ns, not significant. Each dot represents an individual mouse.

investigated whether Id2 deficiency may impact the proportion of Tox⁺CD8⁺T cells exhibiting Tpex features. To address this issue, we investigated the expression of Slamf6 (a surrogate of Tcf1 expression) and Tim-3 in brain-infiltrating PD1⁺Tox⁺CD69⁺CD8⁺T cells.

Remarkably, Id2 deficiency led to a significant increase in the relative proportion of the Slamf6⁺Tim-3⁻ Tpex-like subset (Figure 4E). Finally, no difference was noted between the CD45.1⁺ and the CD45.2⁺ WT Tox⁺PD-1⁺CD69⁺CD8⁺T cell compartments from control chimeras (Figure S5E). Taken
together, our data indicated that Id2 deficiency increased the proportion of exhausted CD8⁺ Trm cells and increased the differentiation of Tpex-like cells during the chronic phase of *T. gondii* OVA infection.

## Id2-forced expression represses Trm exhaustion during chronic *T. gondii* infection

Given that our data had shown an increased frequency of exhausted CD8⁺ Trm cells upon loss of Id2, we wondered whether increasing the Id2 level could repress brain Trm cell exhaustion and rewire the program of exhaustion toward an effector program. Since our model of *T. gondii*-OVA chronic infection yielded only a modest level of CD8⁺ T cell exhaustion and parasite-specific CD8⁺ T cells were protected from exhaustion (Figures 4A and 4B), we wished to set out a second model of *T. gondii* infection leading to an increased level of exhaustion in brain CD8⁺ T cells, including among OVA-specific CD8⁺ T cells. Because CD4⁺ T cell help has been previously shown to repress CD8⁺ T cell exhaustion during *T. gondii* infection,⁴¹ we tested the effect of CD4⁺ T cell depletion on parasite-(OVA)-specific CD8⁺ Trm cell exhaustion. We previously reported that CD4⁺ T cell depletion led to an increase parasite load in the brain during the chronic phase of Tg.GRA6-OVA infection.⁴ As anticipated, CD4⁺ T cell depletion led to an increased level of T cell exhaustion in KᵇOVA-Dex-negative CD44⁺CD8⁺ T cells but also among brain-infiltrating KᵇOVA-Dex⁺ parasite-specific CD8⁺ T cells 35 days post-infection (Figure 5A). Using this experimental setting, we next investigated the impact of Id2 OE on the accumulation and the exhaustion of brain-infiltrating OVA-specific OT-I CD8⁺ T cells (Figure S6A). Strikingly, OT-I cells overexpressing Id2 strongly outnumbered OT-I cells transduced with the control vector both in spleen and in brain 5 weeks post-infection (Figures 5B and 5C). Brain-infiltrating OT-I cells from both groups largely adopted a Trm phenotype coexpressing CD69 and CD49a at this chronic stage of the infection (Figures S6B and S6C). However, Id2 OE reduced the proportion of cells coexpressing PD-1 and Tox among CD69⁺ OT-I cells (Figure 5D). The parasite loads in the brain were similar between mice transferred with control and Id2 OE OT-I cells, as well as the proportion of exhausted cells among the endogenous brain CD8⁺ T cell compartment (Figures S6D and S6E). This indicated that the reduced exhaustion of Id2 OE OT-I cells was intrinsically caused by the increased level of Id2 expression and was not due to differences in antigen load or inflammation, which would have seemingly impacted the phenotype of the endogenous CD8⁺ T cell compartment. T cell exhaustion is characterized by a diminished capacity to coproduce multiple effector cytokines such as IFN-γ and tumor necrosis factor (TNF). Our results showed that brain Id2 OE OT-I Trms (CD69⁺) had an increased proportion of total IFN-γ producers and IFN-γ/TNF double producers, consistent with the induction of an effector-like phenotype and a decreased functional exhaustion (Figure 5E).

The decreased level of T cell exhaustion observed upon Id2 OE during *T. gondii* chronic infection could be explained by a direct impact of Id2 OE to repress the program of T cell exhaustion or, instead, it could reflect an Id2-dependent preferential accumulation of Trms with an effector phenotype over the 5 weeks of infection. Thus, we next asked whether Id2 OE intrin-

sically represses the acquisition of the exhaustion phenotype. To this end, we adapted a previously published protocol of *in vitro* CD8⁺ T cell exhaustion based on repeated antigenic stimulation⁴² (Figure S7A). After 7 days of OVA peptide stimulation, most control and Id2 OE OT-I upregulated PD-1, and a large proportion of them coexpressed Tox, while cells stimulated only once with OVA peptide failed to upregulate these exhaustion markers (Figure S7B). Strikingly, Id2 OE led to a decreased frequency of PD-1⁺Tox⁺ coexpressing cells compared with the control transduced cells, akin to our observations made in the *T. gondii* chronic infection model *in vivo* (Figures S7B–S7D). In addition, Id2 OE partially restored effector functions, with an increased proportion of granzyme B- and IFN-γ-expressing cells, and improved polyfunctionality as shown by the increased proportion of IFN-γ/TNF coproducing cells (Figures S7E–S7G). Collectively, our data showed that forced Id2 expression inhibits T cell exhaustion during chronic *T. gondii* infection and after *in vitro* repeated antigenic stimulation, highlighting its potential as a therapeutic target for maintaining T cell functionality in persistent infections.

## DISCUSSION

Recent single-cell transcriptomic studies have revealed that Trms are a very heterogeneous T cell population during infection, autoimmunity, and tumor development in both humans and mice.⁴,⁹⁻¹³ However, the molecular determinants regulating this phenotypic and functional diversity are not fully understood. In a model of chronic CNS infection with the intracellular parasite *T. gondii*, we demonstrated that Id2 expression levels and its interaction with E2A in pathogen-specific CD8⁺ T cells regulate the balance between the differentiation of effector Trms expressing high levels of effector molecules and of the tissue-retention molecules CD49a, CXCR6, and CD103 and dysfunctional brain Trm cells, which exhibit an exhausted phenotype coupled with a reduced expression of tissue-retention molecules and decreased effector functions. Using single-cell transcriptomic of brain and splenic CD8⁺ T cells isolated from *T. gondii* chronically infected mice, we found that *Id2* expression was more elevated in the Trm cluster showing the highest level of effector molecule and tissue-retention molecule expression. By contrast, among the two most abundant brain Trm clusters identified in our study, the cluster of cells showing the lowest *Id2* expression exhibited an exhausted phenotype, characterized by high expression of *Tox*, *Pdcd1*, and *Tigit*; low levels of genes encoding effector molecules; and lower expression of genes encoding tissue-retention molecules. Using mixed BM chimeras, we showed that T-cell-specific Id2 deficiency led to a decreased development of parasite-specific brain Trm cells expressing CD49a, CXCR6, and CD103 and to reduced effector cytokine and cytotoxic molecule expression. Moreover, the Id2-deficient CD8⁺ T cell compartment was enriched in Trm cells displaying an exhausted phenotype characterized by Tox and PD-1 expression.

Interestingly, a previous meta-analysis of scRNA-seq data of CD8⁺ T cells from the CSF and brain of MS patients has defined a common CD4⁺ and CD8⁺ Trm minimal gene signature that included ID2, suggesting that ID2 could also be important for
A

<figure><img src="image_37.png" /></figure>

B

<figure><img src="image_38.png" /></figure>

C

<figure><img src="image_39.png" /></figure>

D

<figure><img src="image_40.png" /></figure>

E

<figure><img src="image_41.png" /><figcaption>Figure 5. Id2 overexpression represses the exhaustion of parasite-specific Trm during the chronic phase of *T. gondii* upon CD4⁺ T cell depletion</figcaption></figure>

(A) Mice received weekly injection of either an anti-CD4 depleting antibody or an isotype control antibody from day 3 to day 35 p.i. with Tg.GRA6-OVA. Mice were analyzed 5 weeks p.i., and brain and spleen were collected. Bar graph shows the proportion of PD-1⁺TOX⁺-expressing cells in Kᵇ-OVA Dex⁻ or Dex⁺ CD8⁺ T cells from the brain at the chronic stage.

(B–E) Mice were adoptively transferred with OT-I (CD45.1⁺) cells transduced with a control vector or an Id2-overexpressing (Id2 OE) vector expressing the GFP reporter 1 day prior to Tg.GRA6-OVA infection. All mice were treated with the anti-CD4 depleting antibody as in (A). (B) Representative contour plots show the percentage of Ctr and Id2 OE OT-I GFP⁺ among total CD8⁺ T cells from the brain (top) and spleen (bottom). (C) Bar graphs show the frequency among CD8⁺ T cells (left) and total number (right) of Ctr and Id2 OE OT-I GFP⁺ (CD45.1⁺) in the brain and spleen. (D) Representative contour plots (left) and bar graphs (right) show the percentage of PD-1⁺TOX⁺ cells among brain CD69⁺ Id2 OE and Ctr OT-I (CD45.1⁺) cells. (E) Dot plots (left) and bar graphs (right) show the frequency of IFN-γ⁺- and TNF-γ⁺-producing cells in brain Id2 OE and Ctr CD69⁺ OT-I (CD45.1⁺) cells after restimulation with OVA peptide in the presence of monensin or with monensin alone as control.

Data are pooled from two independent experiments. Bars show the mean ± SEM. Statistically significant differences were determined using unpaired t test with Welch correction (A and D), unpaired t test (E, total IFN-γ⁺ and IFN-γ⁺TNF⁺ bar graphs), and Mann-Whitney test (C and E, total TNF⁺ bar graph). \*p < 0.05, \*\*p < 0.01, \*\*\*p < 0.001, and \*\*\*\*p < 0.0001. ns, not significant. Each dot represents an individual mouse.
the generation of CNS-resident Trms in human autoimmune disease. Consistent with this, our analysis has revealed an enrichment of the gene signature of these ITGA1⁺ Trm-like cells from the CSF of MS patients within the Trm cluster expressing the highest level of Id2 in our mouse model of *T. gondii*-infected mice.¹² Moreover the Id2-induced gene signature was also enriched in brain Trms from a mouse model of CNS autoimmunity, reinforcing the hypothesis that Id2 may play a role in the development of brain Trms in various pathophysiological contexts. It remains unclear whether Id2 plays a specific role in the differentiation of brain Trms or if it more broadly contributes to the differentiation of Trms in other anatomical sites. However, the initial description of the Id2 KO mice and recent data on acute LCMV infection have shown that Id2 deficiency led to a loss of IELs of the intestine, hinting at a global role of Id2 in Trm development, although the mechanisms underpinning this loss have not been fully explored.¹⁰,²⁶ Here, our study revealed that, besides its reported role in intestinal Trm homeostasis, Id2 impacts the phenotype and the functions of brain Trms. Indeed, loss of Id2 led to reduced frequencies of CD69⁺ T cell subsets expressing the tissue-retention molecules CD49a and CXCR6 (which are largely coexpressed), with or without CD103, and instead caused the emergence of atypical Trm cells expressing neither of these molecules. Importantly, our scRNA-seq analysis identified *Tcf3* (encoding E2A) as the only E-protein-coding gene expressed in brain Trm clusters from *T. gondii*-infected mice. Moreover, akin to Id2 deficiency, E2A OE in pathogen-specific CD8⁺ T cells resulted in a decreased expression of CD49a and CXCR6. This suggested that Id2 may antagonize E2A transcriptional activity to enable the formation of fully functional Trms capable of long-term retention within the brain. Indeed, CD49a and CXCR6 have been shown to be required for the long-term retention of Trms in various tissues such as the skin or the brain.⁴³⁻⁴⁵ Moreover, decreased CD49a expression could also potentially contribute to the decreased effector functions observed upon Id2 deficiency. Indeed, previous studies have reported that CD49a-deficient Trm cells had reduced IFN-γ expression compared with CD49a-sufficient cells.⁴⁵ Similarly, CD49a⁺CD103⁺ Trms from human psoriatic skin lesions have been shown to possess an increased cytotoxic potential compared with their CD49a-negative counterparts.⁴⁶

Id2, together with Blimp-1 and T-bet, are key transcriptional regulators of effector CD8⁺ T cell differentiation.¹⁸⁻²⁰,²²⁻²⁵ Interestingly, Blimp-1 and T-bet not only promote the acquisition of an effector phenotype but also have been shown to regulate Trm differentiation and T cell exhaustion during infection.¹⁶,¹⁷,⁴⁷,⁴⁸ Indeed, while Blimp-1 and its homolog Hobit are required for Trm differentiation,¹⁶ the downregulation of T-bet (along with Eomes) is necessary to permit transforming growth factor-β (TGF-β) signaling crucial for Trm development.¹⁷ Here, our data showing a role for Id2 in Trm functions reinforce the concept that the effector and the tissue-residency transcriptional programs of CD8⁺ T cell differentiation are tightly interconnected and dependent on similar sets of transcriptional regulators. Moreover, Blimp-1 and T-bet also have divergent roles in the development of terminally exhausted cells, since T-bet deficiency exacerbates T cell dysfunction and increases inhibitory receptor expression,⁴⁸ whereas Blimp-1 deficiency abrogates ter-

minal T cell exhaustion in a dose-dependent manner.⁴⁷ Interestingly, both Blimp-1 and Id2 T cell deficiencies have been previously shown to enhance the differentiation of splenic “follicular cytotoxic CD8⁺ T cells” during chronic LCMV infection. These cells exhibited a phenotype reminiscent of Tpex cells, characterized by the coexpression of PD-1 and TCF-1.²⁹ This is consistent with our results showing that Id2 loss led to an increased proportion of Tox⁺PD-1⁺ exhausted Trm cells displaying a Tpex-like phenotype. The mechanisms by which Id2 antagonizes these Tpex-like Trms is still unclear but could be potentially explained by the previously reported derepression of Id3 and Tcf1 in the absence of Id2. Indeed, both transcriptional regulators have been shown to support Tpex development during LCMV infection.⁴⁹⁻⁵²

Conversely, Id2 OE promoted CD8⁺ T cell accumulation, decreased Tox and PD-1 expression, and led to some recovery of effector functions both during chronic *T. gondii* infection and in an *in vitro* model of T cell exhaustion. These results suggested that the exhaustion program of CD8⁺ T cell differentiation can be rewired by enforcing the effector program through the forced expression of Id2. This finding is in line with recent studies, which have reported that activated STAT5 OE or IL-2 therapy could promote an “effector-like” phenotype in exhausted T cells and repress the Tox-dependent epigenetic and transcriptional program of exhaustion.⁵³⁻⁵⁵ Interestingly, pSTAT5 is a direct transcriptional activator of Id2,²⁵ and Id2 and STAT5 have been shown to be downregulated in a Tox-dependent manner during CNS autoimmunity and chronic viral infection, respectively.³²,⁵³ This raises the question of whether the decrease in T cell exhaustion reported upon interleukin-2 (IL-2) therapeutic administration or after STAT5 forced expression⁵³⁻⁵⁵ could be in part due to the induction of Id2 expression.

Our data showed the absence of exhaustion of KᵇOVA-specific CD8⁺ T cells infiltrating the brain during chronic *T. gondii* infection. By contrast, systemic CD4⁺ T cell depletion led to a marked increase in CD8⁺ T cell exhaustion among OVA-specific CD8⁺ T cells, consistent with previous reports showing the importance of CD4 T cell help in repressing T cell exhaustion during various chronic pathogen infections.⁵⁶⁻⁵⁹ As CD4⁺ T cells have the potential to produce cytokines that are able to induce Id2 in CD8⁺ T cells, such as IL-2 or IL-21,²⁵,⁶⁰ it is tempting to speculate that KᵇOVA-specific CD8⁺ T cells receive a sufficient amount of CD4⁺ T cell help to optimally induce Id2, which in turn represses T cell exhaustion. By contrast, the PD1⁺Tox⁺CD8⁺ T cell population identified among the non-OVA-specific CD8⁺ T cell population may represent CD4 “helpless” CD8⁺ T cells. It would be worthy to determine whether these PD1⁺Tox⁺ T cells are clonally expanded and responding to parasite-derived antigens or, instead, represent a bystander polyclonal CD8⁺ T cell subset.

In summary, our study has identified Id2 as a central regulator of Trm differentiation and function during chronic brain pathogen infection and suggested that Id2 expression level determines the accumulation and the functional fate of brain Trms into either “effector” Trms or “exhausted” Trms. Targeting the Id2-E-protein transcriptional axis could therefore be beneficial either to improve Trm survival and effector functions during chronic CNS pathogen infection or to decrease brain
Trm maintenance and pathogenic functions during CNS autoimmunity.

## Limitations of the study

While our study provides important new insights into the role of Id2 in regulating brain Trm differentiation and exhaustion during chronic *T. gondii* infection, our findings are based on a single pathogen infection system and may not be fully generalizable to other chronic infections in other anatomic sites. Additionally, the use of a constitutive system of Id2 ablation or OE in T cells does not inform on the temporal requirement of Id2 expression in already differentiated Trm cells, and its effects on Trm functions and persistence over time remain to be fully addressed. Indeed, our data have shown that Id2 deficiency functionally impacted the early expression of tissue-retention molecules by CD8⁺ T cells in the spleen, suggesting that Id2 may play a role in the early establishment of the Trm differentiation program impacting not only the formation of CNS Trms but also potentially of Trms residing in other non-lymphoid tissues. Finally, while our bioinformatical analysis suggested a conserved function of Id2 in brain Trms responding to a chronic pathogen and in Trms found in CNS autoimmunity in both humans and mice, future functional studies in CNS models of autoimmunity will be necessary to confirm our findings.

## RESOURCE AVAILABILITY

### Lead contact

Requests for further information and resources and reagents should be directed to and will be fulfilled by the lead contact, Frederick Masson (frederick.masson@inserm.fr).

### Materials availability

This study did not generate new unique reagents.

### Data and code availability

* scRNA-seq data have been deposited at the GEO database and are publicly available as of the date of publication. The accession number is listed in the *key resources table*.

* This study does not report original code.

* Any additional information required to reanalyze the data reported in this work paper is available from the *lead contact* upon request.

## ACKNOWLEDGMENTS

We are indebted to Dr. Gabrielle T. Belz (The Frazer Institute, The University of Queensland, Brisbane, Australia) for the gift of the Id2 floxed mice as well as pMSCV-Id2-IRES-GFP, pMSCV-E47-IRES-mCherry, and related control plasmids. We are grateful to Dr. Klaas Van Gisbergen (Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal) for the gift of the Hobit-TdTomato-Cre-DTR reporter mice, Dr. Corinne Mercier for the gift of the pGRA2/Ble/GRA2 plasmid, and Dr. Sebastian Lourido for expert advice on the generation of ΔGRA2 parasites. Flow cytometry experiments were done at the INFINITY-INSERM UMR1291 core facility connected to the Toulouse Réseau Imagerie network, a member of the France-Biolmaging national infrastructure supported by the French National Research Agency (ANR-10-INBS-04). We are very thankful to Hugo Garnier, Anne-Laure Iscache, Valerie Duplan, and Fatima L'Faqihi for their assistance in cell sorting. We thank the UMS06 for the management of the animal facility and help with animal experimentation. We also thank the platform GetSanté (GENOTOUL, Toulouse, France), in particular Frédéric Martins and Emeline Lhuillier, for their help with the single-cell RNA sequencing libraries.

This work was supported by grants from "Agence Nationale de la Recherche" ANR-19-CE15-0008-01 (TRANSMIT) (to F.M. and N.B.), the PIA PARAFRAP Consortium (ANR-11-LABX0024 to N.B.), "Fondation pour la Recherche sur le Cerveau" AAP2021 to N.B., and "Association de recherche contre le Cancer" (ARC) to A.S.K.C.

## AUTHOR CONTRIBUTIONS

F.M. conceived the study. A.S.K.C., with assistance from L.N., C.T., R.P., E.B., A.H., and M.B., carried out all the experiments. M.A. and N.B. analyzed the scRNA-seq data. F.M. and A.C. were involved in data analysis. F.M. drafted the initial version of the paper, which was subsequently edited by A.C. and N.B.

## DECLARATION OF INTERESTS

The authors declare no competing interests.

## STAR★METHODS

Detailed methods are provided in the online version of this paper and include the following:

* KEY RESOURCES TABLE

* EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

* Mice

* Toxoplasma gondii culture and infection

* METHOD DETAILS

* Generation of bone marrow chimeras

* Isolation and adoptive transfer of OT-I CD8⁺ T cells

* Retroviral transduction of OT-I TCR transgenic T cells

* mAb-depleting treatments

* Isolation of spleen and brain leukocytes

* Flow cytometry

* *In vitro* generation of exhausted CD8⁺ T cells

* T cell restimulation for intracellular cytokine assessment

* *In vitro* generation of Trm-like CD8⁺ T cell

* Parasite load analysis

* Single cell RNA-seq libraries

* Bioinformatical analysis of single-cell RNA-seq data

* QUANTIFICATION AND STATISTICAL ANALYSIS

## SUPPLEMENTAL INFORMATION

Supplemental information can be found online at https://doi.org/10.1016/j.celrep.2025.115861.

Received: September 4, 2024

Revised: March 10, 2025

Accepted: May 28, 2025

Published: June 17, 2025

## REFERENCES

1. Masopust, D., and Soerens, A.G. (2019). Tissue-Resident T Cells and Other Resident Leukocytes. Annu. Rev. Immunol. 37, 521–546. https://doi.org/10.1146/annurev-immunol-042617-053214.

2. van Gisbergen, K.P.J.M., Zens, K.D., and Münz, C. (2021). T-cell memory in tissues. Eur. J. Immunol. 51, 1310–1324. https://doi.org/10.1002/eji.202049062.

3. Gebhardt, T., Palendira, U., Tscharke, D.C., and Bedoui, S. (2018). Tissue-resident memory T cells in tissue homeostasis, persistent infection, and cancer surveillance. Immunol. Rev. 283, 54–76. https://doi.org/10.1111/imr.12650.

4. Porte, R., Belloy, M., Audibert, A., Bassot, E., Aïda, A., Alis, M., Miranda-Capet, R., Jourdes, A., van Gisbergen, K.P.J.M., Masson, F., and
Blanchard, N. (2024). Protective function and differentiation cues of brain-resident CD8+ T cells during surveillance of latent Toxoplasma gondii infection. Proc. Natl. Acad. Sci. USA 121, e2403054121. https://doi.org/10.1073/pnas.2403054121.

5. Okla, K., Farber, D.L., and Zou, W. (2021). Tissue-resident memory T cells in tumor immunity and immunotherapy. J. Exp. Med. 218, e20201605. https://doi.org/10.1084/jem.20201605.

6. Merkler, D., Vincenti, I., Masson, F., and Liblau, R.S. (2022). Tissue-resident CD8 T cells in central nervous system inflammatory diseases: present at the crime scene and, guilty. Curr. Opin. Immunol. 77, 102211. https://doi.org/10.1016/j.coi.2022.102211.

7. Kuric, E., Seiron, P., Krogvold, L., Edwin, B., Buanes, T., Hanssen, K.F., Skog, O., Dahl-Jørgensen, K., and Korsgren, O. (2017). Demonstration of Tissue Resident Memory CD8 T Cells in Insulitic Lesions in Adult Patients with Recent-Onset Type 1 Diabetes. Am. J. Pathol. 187, 581–588. https://doi.org/10.1016/j.ajpath.2016.11.002.

8. Ryan, G.E., Harris, J.E., and Richmond, J.M. (2021). Resident Memory T Cells in Autoimmune Skin Diseases. Front. Immunol. 12, 652191. https://doi.org/10.3389/fimmu.2021.652191.

9. Kurd, N.S., He, Z., Louis, T.L., Milner, J.J., Omilusik, K.D., Jin, W., Tsai, M., Widjaja, C.E., Kanbar, J.N., Olvera, J.G., et al. (2020). Early precursors and molecular determinants of tissue-resident memory CD8(+) T lymphocytes revealed by single-cell RNA sequencing. Sci. Immunol. 5, eaaz6894. https://doi.org/10.1126/sciimmunol.aaz6894.

10. Milner, J.J., Toma, C., He, Z., Kurd, N.S., Nguyen, Q.P., McDonald, B., Quezada, L., Widjaja, C.E., Witherden, D.A., Crowl, J.T., et al. (2020). Heterogenous Populations of Tissue-Resident CD8(+) T Cells Are Generated in Response to Infection and Malignancy. Immunity (Camb., Mass.) 52, 808–824.e7. https://doi.org/10.1016/j.immuni.2020.04.007.

11. Frieser, D., Pignata, A., Khajavi, L., Shlesinger, D., Gonzalez-Fierro, C., Nguyen, X.H., Yermanos, A., Merkler, D., Höftberger, R., Desestret, V., et al. (2022). Tissue-resident CD8(+) T cells drive compartmentalized and chronic autoimmune damage against CNS neurons. Sci. Transl. Med. 14, eabl6157. https://doi.org/10.1126/scitranslmed.abl6157.

12. Ostkamp, P., Deffner, M., Schulte-Mecklenbeck, A., Wünsch, C., Lu, I.N., Wu, G.F., Goelz, S., De Jager, P.L., Kuhlmann, T., Gross, C.C., et al. (2022). A single-cell analysis framework allows for characterization of CSF leukocytes and their tissue of origin in multiple sclerosis. Sci. Transl. Med. 14, eadc9778. https://doi.org/10.1126/scitranslmed.adc9778.

13. Savas, P., Virassamy, B., Ye, C., Salim, A., Mintoff, C.P., Caramia, F., Salgado, R., Byrne, D.J., Teo, Z.L., Dushyanthen, S., et al. (2018). Single-cell profiling of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis. Nat. Med. 24, 986–993. https://doi.org/10.1038/s41591-018-0078-7.

14. Shallberg, L.A., Phan, A.T., Christian, D.A., Perry, J.A., Haskins, B.E., Beiting, D.P., Harris, T.H., Koshy, A.A., and Hunter, C.A. (2022). Impact of secondary TCR engagement on the heterogeneity of pathogen-specific CD8+ T cell response during acute and chronic toxoplasmosis. PLoS Pathog. 18, e1010296. https://doi.org/10.1371/journal.ppat.1010296.

15. Milner, J.J., Toma, C., Yu, B., Zhang, K., Omilusik, K., Phan, A.T., Wang, D., Getzler, A.J., Nguyen, T., Crotty, S., et al. (2017). Runx3 programs CD8(+) T cell residency in non-lymphoid tissues and tumours. Nature 552, 253–257. https://doi.org/10.1038/nature24993.

16. Mackay, L.K., Minnich, M., Kragten, N.A.M., Liao, Y., Nota, B., Seillet, C., Zaid, A., Man, K., Preston, S., Freestone, D., et al. (2016). Hobit and Blimp1 instruct a universal transcriptional program of tissue residency in lymphocytes. Sci. Technol. Humanit. 352, 459–463. https://doi.org/10.1126/science.aad2035.

17. Mackay, L.K., Wynne-Jones, E., Freestone, D., Pellicci, D.G., Mielke, L.A., Newman, D.M., Braun, A., Masson, F., Kallies, A., Belz, G.T., and Carbone, F.R. (2015). T-box Transcription Factors Combine with the Cytokines TGF-beta and IL-15 to Control Tissue-Resident Memory T Cell Fate. Immunity (Camb., Mass.) 43, 1101–1111. https://doi.org/10.1016/j.immuni.2015.11.008.

18. Joshi, N.S., Cui, W., Chandele, A., Lee, H.K., Urso, D.R., Hagman, J., Gapin, L., and Kaech, S.M. (2007). Inflammation directs memory precursor and short-lived effector CD8(+) T cell fates via the graded expression of T-bet transcription factor. Immunity (Camb., Mass.) 27, 281–295.

19. Kallies, A., Xin, A., Belz, G.T., and Nutt, S.L. (2009). Blimp-1 transcription factor is required for the differentiation of effector CD8(+) T cells and memory responses. Immunity (Camb., Mass.) 31, 283–295.

20. Xin, A., Masson, F., Liao, Y., Preston, S., Guan, T., Gloury, R., Olshansky, M., Lin, J.X., Li, P., Speed, T.P., et al. (2016). A molecular threshold for effector CD8(+) T cell differentiation controlled by transcription factors Blimp-1 and T-bet. Nat. Immunol. 17, 422–432. https://doi.org/10.1038/ni.3410.

21. Cruz-Guillot, F., Pipkin, M.E., Djuretic, I.M., Levanon, D., Lotem, J., Lichtenheld, M.G., Groner, Y., and Rao, A. (2009). Runx3 and T-box proteins cooperate to establish the transcriptional program of effector CTLs. J. Exp. Med. 206, 51–59. https://doi.org/10.1084/jem.20081242.

22. Cannarile, M.A., Lind, N.A., Rivera, R., Sheridan, A.D., Camfield, K.A., Wu, B.B., Cheung, K.P., Ding, Z., and Goldrath, A.W. (2006). Transcriptional regulator Id2 mediates CD8 + T cell immunity. Nat. Immunol. 7, 1317–1325.

23. Knell, J., Best, J.A., Lind, N.A., Yang, E., D'Cruz, L.M., and Goldrath, A.W. (2013). Id2 influences differentiation of killer cell lectin-like receptor G1(hi) short-lived CD8+ effector T cells. J. Immunol. 190, 1501–1509. https://doi.org/10.4049/jimmunol.1200750.

24. Masson, F., Minnich, M., Olshansky, M., Bilic, I., Mount, A.M., Kallies, A., Speed, T.P., Busslinger, M., Nutt, S.L., and Belz, G.T. (2013). Id2-mediated inhibition of E2A represses memory CD8+ T cell differentiation. J. Immunol. 190, 4585–4594. https://doi.org/10.4049/jimmunol.1300099.

25. Yang, C.Y., Best, J.A., Knell, J., Yang, E., Sheridan, A.D., Jesionek, A.K., Li, H.S., Rivera, R.R., Lind, K.C., D'Cruz, L.M., et al. (2011). The transcriptional regulators Id2 and Id3 control the formation of distinct memory CD8+ T cell subsets. Nat. Immunol. 12, 1221–1229. https://doi.org/10.1038/ni.2158.

26. Kim, J.K., Takeuchi, M., and Yokota, Y. (2004). Impairment of intestinal intraepithelial lymphocytes in Id2 deficient mice. Gut 53, 480–486. https://doi.org/10.1136/gut.2003.022293.

27. Yao, C., Sun, H.W., Lacey, N.E., Ji, Y., Moseman, E.A., Shih, H.Y., Heuston, E.F., Kirby, M., Anderson, S., Cheng, J., et al. (2019). Single-cell RNA-seq reveals TOX as a key regulator of CD8(+) T cell persistence in chronic infection. Nat. Immunol. 20, 890–901. https://doi.org/10.1038/s41590-019-0403-4.

28. Zheng, L., Qin, S., Si, W., Wang, A., Xing, B., Gao, R., Ren, X., Wang, L., Wu, X., Zhang, J., et al. (2021). Pan-cancer single-cell landscape of tumor-infiltrating T cells. Sci. Technol. Humanit. 374, abe6474. https://doi.org/10.1126/science.abe6474.

29. Leong, Y.A., Chen, Y., Ong, H.S., Wu, D., Man, K., Deleage, C., Minnich, M., Meckiff, B.J., Wei, Y., Hou, Z., et al. (2016). CXCR5(+) follicular cytotoxic T cells control viral infection in B cell follicles. Nat. Immunol. 17, 1187–1196. https://doi.org/10.1038/ni.3543.

30. Alfei, F., Kanev, K., Hofmann, M., Wu, M., Ghoneim, H.E., Roelli, P., Utzschneider, D.T., von Hoesslin, M., Cullen, J.G., Fan, Y., et al. (2019). TOX reinforces the phenotype and longevity of exhausted T cells in chronic viral infection. Nature 571, 265–269. https://doi.org/10.1038/s41586-019-1326-9.

31. Page, N., Lemeille, S., Vincenti, I., Klimek, B., Mariotte, A., Wagner, I., Di Liberto, G., Kaye, J., and Merkler, D. (2021). Persistence of self-reactive CD8+ T cells in the CNS requires TOX-dependent chromatin remodeling. Nat. Commun. 12, 1009. https://doi.org/10.1038/s41467-021-21109-3.

32. Page, N., Klimek, B., De Roo, M., Steinbach, K., Soldati, H., Lemeille, S., Wagner, I., Kreutzfeldt, M., Di Liberto, G., Vincenti, I., et al. (2019). Expression of the DNA-Binding Factor TOX Promotes the Encephalitogenic Potential of Microbe-Induced Autoreactive CD8(+) T Cells. Immunity (Camb., Mass.) 50, 763. https://doi.org/10.1016/j.immuni.2019.02.011.
33. Salvioni, A., Belloy, M., Lebourg, A., Bassot, E., Cantaloube-Ferrieu, V., Vasseur, V., Blanié, S., Liblau, R.S., Suberbielle, E., Robey, E.A., and Blanchard, N. (2019). Robust Control of a Brain-Persisting Parasite through MHC I Presentation by Infected Neurons. Cell Rep. 27, 3254-3268.e8. https://doi.org/10.1016/j.celrep.2019.05.051.

34. Landrith, T.A., Sureshchandra, S., Rivera, A., Jang, J.C., Rais, M., Nair, M. G., Messaoudi, I., and Wilson, E.H. (2017). CD103(+) CD8 T Cells in the Toxoplasma-Infected Brain Exhibit a Tissue-Resident Memory Transcriptional Profile. Front. Immunol. 8, 335. https://doi.org/10.3389/fimmu.2017.00335.

35. Hudson, W.H., Gensheimer, J., Hashimoto, M., Wieland, A., Valanparambil, R.M., Li, P., Lin, J.X., Konieczny, B.T., Im, S.J., Freeman, G.J., et al. (2019). Proliferating Transitory T Cells with an Effector-like Transcriptional Signature Emerge from PD-1(+) Stem-like CD8(+) T Cells during Chronic Infection. Immunity (Camb., Mass.) 51, 1043-1058.e4. https://doi.org/10.1016/j.immuni.2019.11.002.

36. Lopez, J., Bittame, A., Massera, C., Vasseur, V., Effantin, G., Valat, A., Buaillon, C., Allart, S., Fox, B.A., Rommereim, L.M., et al. (2015). Intravascular Membranes Regulate CD8 T Cell Recognition of Membrane-Bound Toxoplasma gondii Protective Antigen. Cell Rep. 13, 2273-2286. https://doi.org/10.1016/j.celrep.2015.11.001.

37. Park, S.L., Christo, S.N., Wells, A.C., Gandolfo, L.C., Zaid, A., Alexandre, Y.O., Burn, T.N., Schröder, J., Collins, N., Han, S.J., et al. (2023). Divergent molecular networks program functionally distinct CD8(+) skin-resident memory T cells. Sci. Technol. Humanit. 382, 1073-1079. https://doi.org/10.1126/science.adl8885.

38. Behr, F.M., Parga-Vidal, L., Kragten, N.A.M., van Dam, T.J.P., Wesselink, T.H., Sheridan, B.S., Arens, R., van Lier, R.A.W., Stark, R., and van Gisbergen, K.P.J.M. (2020). Tissue-resident memory CD8(+) T cells shape local and systemic secondary T cell responses. Nat. Immunol. 21, 1070-1081. https://doi.org/10.1038/s41590-020-0723-4.

39. Chu, H.H., Chan, S.W., Gosling, J.P., Blanchard, N., Tsitsiklis, A., Lythe, G., Shastri, N., Molina-París, C., and Robey, E.A. (2016). Continuous Effector CD8(+) T Cell Production in a Controlled Persistent Infection Is Sustained by a Proliferative Intermediate Population. Immunity (Camb., Mass.) 45, 159-171. https://doi.org/10.1016/j.immuni.2016.06.013.

40. Wilson, D.C., Grotenbreg, G.M., Liu, K., Zhao, Y., Frickel, E.M., Gubbels, M.J., Ploegh, H.L., and Yap, G.S. (2010). Differential regulation of effector- and central-memory responses to Toxoplasma gondii Infection by IL-12 revealed by tracking of Tgdt057-specific CD8+ T cells. PLoS Pathog. 6, e1000815. https://doi.org/10.1371/journal.ppat.1000815.

41. Hwang, S., Cobb, D.A., Bhadra, R., Youngblood, B., and Khan, I.A. (2016). Blimp-1-mediated CD4 T cell exhaustion causes CD8 T cell dysfunction during chronic toxoplasmosis. J. Exp. Med. 213, 1799-1818. https://doi.org/10.1084/jem.20151995.

42. Zhao, M., Kiernan, C.H., Stairiker, C.J., Hope, J.L., Leon, L.G., van Meurs, M., Brouwers-Haspels, I., Boers, R., Boers, J., Gribnau, J., et al. (2020). Rapid in vitro generation of bona fide exhausted CD8+ T cells is accompanied by Tcf7 promotor methylation. PLoS Pathog. 16, e1008555. https://doi.org/10.1371/journal.ppat.1008555.

43. Evrard, M., Becht, E., Fonseca, R., Obers, A., Park, S.L., Ghabdan-Zanlugu, N., Schroeder, J., Christo, S.N., Schienstock, D., Lai, J., et al. (2023). Single-cell protein expression profiling resolves circulating and resident memory T cell diversity across tissues and infection contexts. Immunity (Camb., Mass.) 56, 1664-1680.e9. https://doi.org/10.1016/j.immuni.2023.06.005.

44. Rosen, S.F., Soung, A.L., Yang, W., Ai, S., Kanmogne, M., Davé, V.A., Artyomov, M., Magee, J.A., and Klein, R.S. (2022). Single-cell RNA transcriptome analysis of CNS immune cells reveals CXCL16/CXCR6 as maintenance factors for tissue-resident T cells that drive synapse elimination. Genome Med. 14, 108. https://doi.org/10.1186/s13073-022-01111-0.

45. Bromley, S.K., Akbaba, H., Mani, V., Mora-Buch, R., Chasse, A.Y., Sama, A., and Luster, A.D. (2020). CD49a Regulates Cutaneous Resident Memory

CD8(+) T Cell Persistence and Response. Cell Rep. 32, 108085. https://doi.org/10.1016/j.celrep.2020.108085.

46. Cheuk, S., Schlums, H., Gallais Sérézal, I., Martini, E., Chiang, S.C., Marquardt, N., Gibbs, A., Detlofsson, E., Introini, A., Forkel, M., et al. (2017). CD49a Expression Defines Tissue-Resident CD8(+) T Cells Poised for Cytotoxic Function in Human Skin. Immunity (Camb., Mass.) 46, 287-300. https://doi.org/10.1016/j.immuni.2017.01.009.

47. Shin, H., Blackburn, S.D., Intlekofer, A.M., Kao, C., Angelosanto, J.M., Reiner, S.L., and Wherry, E.J. (2009). A role for the transcriptional repressor Blimp-1 in CD8(+) T cell exhaustion during chronic viral infection. Immunity (Camb., Mass.) 31, 309-320. https://doi.org/10.1016/j.immuni.2009.06.019.

48. Kao, C., Oestreich, K.J., Paley, M.A., Crawford, A., Angelosanto, J.M., Ali, M.A.A., Intlekofer, A.M., Boss, J.M., Reiner, S.L., Weinmann, A.S., and Wherry, E.J. (2011). Transcription factor T-bet represses expression of the inhibitory receptor PD-1 and sustains virus-specific CD8+ T cell responses during chronic infection. Nat. Immunol. 12, 663-671. https://doi.org/10.1038/ni.2046.

49. Utzschneider, D.T., Charmoy, M., Chennupati, V., Pousse, L., Ferreira, D. P., Calderon-Copete, S., Danilo, M., Alfei, F., Hofmann, M., Wieland, D., et al. (2016). T Cell Factor 1-Expressing Memory-like CD8(+) T Cells Sustain the Immune Response to Chronic Viral Infections. Immunity (Camb., Mass.) 45, 415-427. https://doi.org/10.1016/j.immuni.2016.07.021.

50. Chen, Z., Ji, Z., Ngiow, S.F., Manne, S., Cai, Z., Huang, A.C., Johnson, J., Staupe, R.P., Bengsch, B., Xu, C., et al. (2019). TCF-1-Centered Transcriptional Network Drives an Effector versus Exhausted CD8 T Cell-Fate Decision. Immunity (Camb., Mass.) 51, 840-855.e5. https://doi.org/10.1016/j.immuni.2019.09.013.

51. Gago da Graca, C., Sheikh, A.A., Newman, D.M., Wen, L., Li, S., Shen, J., Zhang, Y., Gabriel, S.S., Chisanga, D., Seow, J., et al. (2025). Stem-like memory and precursors of exhausted T cells share a common progenitor defined by ID3 expression. Sci. Immunol. 10, eadn1945. https://doi.org/10.1126/sciimmunol.adn1945.

52. Ran, L., Yue, Z., Ran, M., Liu, Q., Su, X., Wang, L., Wen, S., Xu, L., Lei, S., Ou, Z., et al. (2024). The transcription regulator ID3 maintains tumor-specific memory CD8(+) T cells in draining lymph nodes during tumorigenesis. Cell Rep. 43, 114690. https://doi.org/10.1016/j.celrep.2024.114690.

53. Beltra, J.C., Abdel-Hakeem, M.S., Manne, S., Zhang, Z., Huang, H., Kuraichi, M., Su, L., Picton, L., Ngiow, S.F., Muroyama, Y., et al. (2023). Stat5 opposes the transcription factor Tox and rewires exhausted CD8(+) T cells toward durable effector-like states during chronic antigen exposure. Immunity (Camb., Mass.) 56, 2699-2718.e11. https://doi.org/10.1016/j.immuni.2023.11.005.

54. Hashimoto, M., Araki, K., Cardenas, M.A., Li, P., Jadhav, R.R., Kissick, H. T., Hudson, W.H., McGuire, D.J., Obeng, R.C., Wieland, A., et al. (2022). PD-1 combination therapy with IL-2 modifies CD8(+) T cell exhaustion program. Nature 610, 173-181. https://doi.org/10.1038/s41586-022-05257-0.

55. Codarri Deak, L., Nicolini, V., Hashimoto, M., Karagianni, M., Schwalie, P. C., Lauener, L., Varypataki, E.M., Richard, M., Bommer, E., Sam, J., et al. (2022). PD-1-cis IL-2R agonism yields better effectors from stem-like CD8 (+) T cells. Nature 610, 161-172. https://doi.org/10.1038/s41586-022-05192-0.

56. Moretto, M.M., Hwang, S., and Khan, I.A. (2017). Downregulated IL-21 Response and T Follicular Helper Cell Exhaustion Correlate with Compromised CD8 T Cell Immunity during Chronic Toxoplasmosis. Front. Immunol. 8, 1436. https://doi.org/10.3389/fimmu.2017.01436.

57. Barber, D.L., Wherry, E.J., Masopust, D., Zhu, B., Allison, J.P., Sharpe, A. H., Freeman, G.J., and Ahmed, R. (2006). Restoring function in exhausted CD8 T cells during chronic viral infection. Nature 439, 682-687. https://doi.org/10.1038/nature04444.

58. Lu, Y.J., Barreira-Silva, P., Boyce, S., Powers, J., Cavallo, K., and Behar, S.M. (2021). CD4 T cell help prevents CD8 T cell exhaustion and promotes
control of Mycobacterium tuberculosis infection. Cell Rep. 36, 109696.
https://doi.org/10.1016/j.celrep.2021.109696.

59. Frank, G.M., Lepisto, A.J., Freeman, M.L., Sheridan, B.S., Cherpes, T.L., and Hendricks, R.L. (2010). Early CD4(+) T cell help prevents partial CD8 (+) T cell exhaustion and promotes maintenance of Herpes Simplex Virus 1 latency. J. Immunol. 184, 277-286. https://doi.org/10.4049/jimmunol.0902373.

60. Kishida, T., Hiromura, Y., Shin-Ya, M., Asada, H., Kuriyama, H., Sugai, M., Shimizu, A., Yokota, Y., Hama, T., Imanishi, J., et al. (2007). IL-21 induces inhibitor of differentiation 2 and leads to complete abrogation of anaphylaxis in mice. J. Immunol. 179, 8554-8561. https://doi.org/10.4049/jimmunol.179.12.8554.

61. Masson, F., Ghisi, M., Groom, J.R., Kallies, A., Seillet, C., Johnstone, R.W., Nutt, S.L., and Belz, G.T. (2014). Id2 represses E2A-mediated activation of IL-10 expression in T cells. Blood 123, 3420-3428. https://doi.org/10.1182/blood-2014-03-561456.

62. Shen, B., Brown, K.M., Lee, T.D., and Sibley, L.D. (2014). Efficient gene disruption in diverse strains of Toxoplasma gondii using CRISPR/CAS9. mBio 5, e01114. https://doi.org/10.1128/mBio.01114-14.

63. Sidik, S.M., Huet, D., Ganesan, S.M., Huynh, M.H., Wang, T., Nasamu, A. S., Thiru, P., Saeij, J.P.J., Carruthers, V.B., Niles, J.C., and Lourido, S. (2016). A Genome-wide CRISPR Screen in Toxoplasma Identifies Essential Apicomplexan Genes. Cell 166, 1423-1435.e12. https://doi.org/10.1016/j.cell.2016.08.019.

64. Mercier, C., Howe, D.K., Mordue, D., Lingnau, M., and Sibley, L.D. (1998). Targeted disruption of the GRA2 locus in Toxoplasma gondii decreases

acute virulence in mice. Infect. Immun. 66, 4176-4182. https://doi.org/10.1128/iai.66.9.4176-4182.1998.

65. Feliu, V., Vasseur, V., Grover, H.S., Chu, H.H., Brown, M.J., Wang, J., Boyle, J.P., Robey, E.A., Shastri, N., and Blanchard, N. (2013). Location of the CD8 T cell epitope within the antigenic precursor determines immunogenicity and protection against the Toxoplasma gondii parasite. PLoS Pathog. 9, e1003449. https://doi.org/10.1371/journal.ppat.1003449.

66. Zheng, G.X.Y., Terry, J.M., Belgrader, P., Ryvkin, P., Bent, Z.W., Wilson, R., Ziraldo, S.B., Wheeler, T.D., McDermott, G.P., Zhu, J., et al. (2017). Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049. https://doi.org/10.1038/ncomms14049.

67. Hao, Y., Hao, S., Andersen-Nissen, E., Mauck, W.M., 3rd, Zheng, S., Butler, A., Lee, M.J., Wilk, A.J., Darby, C., Zager, M., et al. (2021). Integrated analysis of multimodal single-cell data. Cell 184, 3573-3587.e29. https://doi.org/10.1016/j.cell.2021.04.048.

68. Korotkevich, G., Sukhov, V., Budin, N., Shpak, B., Artyomov, M.N., and Sergushichev, A. (2021). Fast gene set enrichment analysis. Preprint at bioRxiv. https://doi.org/10.1101/060012.

69. Subramanian, A., Tamayo, P., Mootha, V.K., Mukherjee, S., Ebert, B.L., Gillette, M.A., Paulovich, A., Pomeroy, S.L., Golub, T.R., Lander, E.S., and Mesirov, J.P. (2005). Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545-15550. https://doi.org/10.1073/pnas.0506580102.
## STAR★METHODS

### KEY RESOURCES TABLE

<table><thead><tr><th>REAGENT or RESOURCE</th><th>SOURCE</th><th>IDENTIFIER</th></tr></thead><tbody><tr><td colspan="3">Antibodies</td></tr><tr><td>CD45.1</td><td>Thermofisher</td><td>Cat # 48-0453-82, Clone A20, RRID:AB_1272189</td></tr><tr><td>CD45.1</td><td>BD</td><td>Cat # 561235, Clone A20, RRID:AB_10611577</td></tr><tr><td>CD45.1</td><td>BD</td><td>Cat # 741093, Clone A20, RRID:AB_2870692</td></tr><tr><td>CD45.2</td><td>BD</td><td>Cat # 552950, Clone 104, RRID:AB_394528</td></tr><tr><td>CD45.2</td><td>BD</td><td>Cat # 560693, Clone 104, RRID:AB_1727491</td></tr><tr><td>CD45.2</td><td>Biolegend</td><td>Cat # 109816, Clone 104, RRID:AB_492868</td></tr><tr><td>CXCR6</td><td>Thermofisher</td><td>Cat # 46-9186-82, Clone DANID2, RRID:AB_2734902</td></tr><tr><td>CD8</td><td>BD</td><td>Cat # 563332, Clone 53-6.7, RRID:AB_2721167</td></tr><tr><td>CD8</td><td>BD</td><td>Cat # 563898, Clone 53-6.7, RRID:AB_2738474</td></tr><tr><td>CD8</td><td>BD</td><td>Cat # 553035, Clone 53-6.7, RRID:AB_398527</td></tr><tr><td>CD8</td><td>Biolegend</td><td>Cat # 100722, Clone 53-6.7, RRID:AB_312760</td></tr><tr><td>CD8</td><td>BD</td><td>Cat # 612898, Clone 53-6.7, RRID:AB_2870186</td></tr><tr><td>CD3e</td><td>BD</td><td>Cat # 561388, Clone 17A2, RRID:AB_10642588</td></tr><tr><td>CD3e</td><td>Biolegend</td><td>Cat # 100349, Clone 145-2C11, RRID:AB_2565841</td></tr><tr><td>CD62L</td><td>BD</td><td>Cat # 553152, Clone MEL-14, RRID:AB_398533</td></tr><tr><td>CD62L</td><td>BD</td><td>Cat # 741230, Clone MEL-14, RRID:AB_2870784</td></tr><tr><td>CD44</td><td>Thermofisher</td><td>Cat # 56-0441-82, Clone IM7, RRID:AB_494011</td></tr><tr><td>CD44</td><td>Thermofisher</td><td>Cat # 45-0441-82, Clone IM7, RRID:AB_925746</td></tr><tr><td>CD44</td><td>Biolegend</td><td>Cat # 103037, Clone IM7, RRID:AB_10900641</td></tr><tr><td>PD-1 (CD279)</td><td>Biolegend</td><td>Cat # 109116, Clone RMP1-30, RRID:AB_2566547</td></tr><tr><td>PD-1 (CD279)</td><td>BD</td><td>Cat # 744548, Clone J43, RRID:AB_2742319</td></tr><tr><td>Slamf6 (Ly108)</td><td>BD</td><td>Cat # 741030, Clone 13G3, RRID:AB_2740648</td></tr><tr><td>Slamf6 (Ly108)</td><td>Biolegend</td><td>Cat # 134608, Clone 330-AJ, RRID:AB_2188093</td></tr><tr><td>Tim3 (CD366)</td><td>BD</td><td>Cat # 747619, Clone 5D12/TIM-3, RRID:AB_2744185</td></tr><tr><td>CD69</td><td>Thermofisher</td><td>Cat # 25-0691-82, Clone H1.2F3, RRID:AB_469637</td></tr><tr><td>CD69</td><td>BD</td><td>Cat # 751593, Clone H1.2F3, RRID:AB_2875587</td></tr><tr><td>CD103</td><td>BD</td><td>Cat # 563087, Clone M290, RRID:AB_2721775</td></tr><tr><td>CD49a</td><td>BD</td><td>Cat # 741776, Clone Ha31/8, RRID:AB_2871130</td></tr><tr><td>TOX</td><td>Miltenyi</td><td>Cat # 130-118-335, Clone REA473, RRID:AB_2751485</td></tr><tr><td>Granzyme B</td><td>Thermofisher</td><td>Cat # 12-8898-82, Clone NGZB, RRID:AB_10870787</td></tr><tr><td>Granzyme B</td><td>Biolegend</td><td>Cat # 515406, Clone GB11, RRID:AB_2294995</td></tr><tr><td>IFN-γ</td><td>BD</td><td>Cat # 563773, Clone XMG1.2, RRID:AB_2738419</td></tr><tr><td>TNF</td><td>BD</td><td>Cat # 558000, Clone MP6-XT22, RRID:AB_396980</td></tr><tr><td>H-2 Kb-SIINFEKL (OVA)</td><td>Immudex</td><td>Cat # JD2163</td></tr><tr><td>InVivoPlus anti-mouse CD4</td><td>BioXcell</td><td>Cat # BP0003-1, Clone GK1.5, RRID:AB_1107636</td></tr><tr><td>InVivoPlus rat IgG2b</td><td>BioXcell</td><td>Cat # BP0090, Clone LTF-2, RRID:AB_1107780</td></tr><tr><td colspan="3">Bacterial and virus strains</td></tr><tr><td>Toxoplasma gondii (Pru.GFP.GRA6-OVA)</td><td>Salvioni et al., 2019<sup>23</sup></td><td>N/A</td></tr><tr><td>Toxoplasma gondii (Pru.ΔGRA2.GRA6-OVA)</td><td>Lopez et al., 2015<sup>36</sup></td><td>N/A</td></tr><tr><td colspan="3">Chemicals, peptides, and recombinant proteins</td></tr><tr><td>PMA (phorbol 12-myristate 13-acetate)</td><td>Sigma-Aldrich</td><td>Cat # P8139</td></tr><tr><td>Ionomycin</td><td>Sigma-Aldrich</td><td>Cat # I0634</td></tr><tr><td>Protein Transport Inhibitor (Containing Monensin)</td><td>BD</td><td>Cat # 554724</td></tr></tbody></table>

(Continued on next page)
<figure><img src="image_42.png" /></figure>

Continued

<table><thead><tr><td>REAGENT or RESOURCE</td><td>SOURCE</td><td>IDENTIFIER</td></tr></thead><tbody><tr><td>Collagenase D</td><td>Roche</td><td>Cat # 11088882001</td></tr><tr><td>DNase I</td><td>Sigma</td><td>Cat # DN25</td></tr><tr><td>Percoll</td><td>GE Healthcare</td><td>Cat # 17-0891-01</td></tr><tr><td>RetroNectin</td><td>Takara</td><td>Cat # T202</td></tr><tr><td>Polybrene</td><td>R&D</td><td>Cat # 7711</td></tr><tr><td>Human IL-2 Recombinant</td><td>Peprotech</td><td>Cat # 200-02</td></tr><tr><td>Mouse IL-7 Recombinant</td><td>Peprotech</td><td>Cat # 217-07</td></tr><tr><td>Mouse IL-15 Recombinant</td><td>Peprotech</td><td>Cat # 210-15</td></tr><tr><td>Mouse IL-12 p70 Recombinant</td><td>Peprotech</td><td>Cat # 210-12</td></tr><tr><td>Mouse IL-33 Recombinant</td><td>Peprotech</td><td>Cat # 210-33</td></tr><tr><td>Human TGF-beta 1 Recombinant</td><td>Peprotech</td><td>Cat # 100-21</td></tr><tr><td>OVA peptide</td><td>Genescust</td><td>N/A</td></tr></tbody></table>

Critical commercial assays

<table><tr><td>Dynabeads Untouched Mouse CD8 Cells Kit</td><td>Invitrogen</td><td>Cat # 11417D</td></tr><tr><td>CD8α T Cell Isolation Kit</td><td>Miltenyi</td><td>Cat # 130-104-075</td></tr><tr><td>Cytofix/Cytoperm Kit</td><td>BD Biosciences</td><td>Cat # 554714</td></tr><tr><td>Foxp3/Transcription Factor Staining Buffer Set</td><td>eBioscience</td><td>Cat # 00-5523-00</td></tr></table>

Deposited data

<table><tr><td>Single-cell RNA seq</td><td>This paper</td><td>GEO:GSE270492</td></tr></table>

Experimental models: Organisms/strains

<table><tr><td>C57BL/6J (Pptrc<sup>b/b</sup>) mice</td><td>Janvier-Labs</td><td>N/A</td></tr><tr><td>Id2 floxed x CD4<sup>Cre+</sup>, Id2<sup>fl/fl</sup>CD4<sup>Cre+</sup>, or Id2<sup>+/+</sup>CD4<sup>Cre+</sup>)</td><td>In house</td><td>N/A</td></tr><tr><td>C57BL/6 CD45.1 x CD45.2 mice (Pptrc<sup>a/a</sup> or Pptrc<sup>a/b</sup>)</td><td>In house</td><td>N/A</td></tr><tr><td>OT-I x C57BL/6 CD45.1 mice (OT-I<sup>Tg/+</sup>; Pptrc<sup>a/a</sup>)</td><td>In house</td><td>N/A</td></tr><tr><td>OT-I x Hobit-TdTomato-Cre-DTR x C57BL/6 CD45.1 mice (OT-I<sup>Tg/+</sup>; Pptrc<sup>a/a</sup>; Hobit<sup>Cre/+</sup>)</td><td>In house</td><td>N/A</td></tr></table>

Oligonucleotides

<table><tr><td>TOX 9</td><td>Sigma</td><td>5'-AGGAGAGATATCAGGACTGTAG</td></tr><tr><td>TOX 11</td><td>Sigma</td><td>5'-GCGTCGTCTCGTCTAGATCG</td></tr></table>

Recombinant DNA

<table><tr><td>pMSCV-Id2-IRES-GFP</td><td>Masson et al.<sup>24</sup></td><td>N/A</td></tr><tr><td>pMSCV-IRES-GFP</td><td>Masson et al.<sup>24</sup></td><td>N/A</td></tr><tr><td>pMSCV-Tcfe2a-IRES-mCherry</td><td>Masson et al.<sup>61</sup></td><td>N/A</td></tr><tr><td>pMSCV-IRES-mCherry</td><td>Masson et al.<sup>61</sup></td><td>N/A</td></tr></table>

Software and algorithms

<table><tr><td>CellRanger</td><td>10X Genomics</td><td>Version 4.0.3</td></tr><tr><td>Seurat</td><td>Satija Lab</td><td>Version 4.2.1</td></tr><tr><td>FlowJo</td><td>FlowJo LLC</td><td>Version 10.9.0</td></tr><tr><td>Prism</td><td>GraphPad</td><td>Version 10.1.2</td></tr><tr><td>Inkscape</td><td>Inkscape</td><td>Version 1.4</td></tr><tr><td>Adobe Illustrator CC</td><td>Adobe</td><td>Version 21.1.0</td></tr><tr><td>Endnote</td><td>Endnote</td><td>Version 7</td></tr><tr><td>GSEA Mac App</td><td>Broad Institute</td><td>Version 4.4.0</td></tr></table>
## EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

### Mice

C57BL/6J CD45.2⁺ (*Ptprc*<sup>b/b</sup>) were from Janvier-Labs, *Id2* floxed<sup>24</sup> x *CD4*cre mice either *Id2* TKO (*Id2*<sup>fl/fl</sup>*CD4*<sup>Cre+</sup>), or *Id2* WT littermates (*Id2*<sup>fl/+</sup>*CD4*<sup>Cre-</sup> and *Id2*<sup>+/+</sup>*CD4*<sup>Cre+</sup>), C57BL/6 CD45.1 x CD45.2 (*Ptprc*<sup>a/a</sup> and *Ptprc*<sup>a/b</sup>) mice, OT-I TCR transgenic x C57BL/6 CD45.1 (OT-I<sup>Tg/+</sup>/*Ptprc*<sup>a/a</sup>) and OT-I x Hobit-TdTomato-Cre-DTR<sup>38</sup> x C57BL/6 CD45.1 mice (OT-I<sup>Tg/+</sup>/*Ptprc*<sup>a/a</sup>/*Hobit*<sup>Cre/+</sup>) were bred in house at the US006 animal facility. Mice were all males in a C57BL/6J background. Mice used for OT-I cell adoptive transfer experiments and bone marrow chimeras experiments were 7-8 weeks old at the beginning of the experiment and were analyzed between 9-26 weeks of age depending on the experimental conditions. As only males were used in this study, we acknowledge that there could be some possible sex-related bias. All mice were bred and maintained under specific pathogen-free conditions in accordance with the guidelines of the French National Veterinary Services and the European regulations (EEC Council Directive, 2010/63/EU, September 2010) after the approval by the local animal experimentation ethics committee CEEA122.

### Toxoplasma gondii culture and infection

For all experiments, GFP⁺ type II Prugnaud (Pru) *T. gondii*, expressing GRA6-OVA under the control of the endogenous GRA6 promoter (Pru.GFP.GRA6-OVA<sup>33</sup> or its derivative Pru.ΔGRA2.GRA6-OVA<sup>36</sup>) were used. The GRA2-deficient Pru.ΔGRA2-GRA6-OVA parasites were engineered from the parental Pru.GFP.GRA6-OVA by CRISPR/Cas9-mediated suppression of the GRA2 gene, using phleomycin selection. In brief, Pru.GFP.GRA6-OVA tachyzoites were co-transfected by electroporation (1:1 ratio) with one plasmid coding for both Cas9 and a sgRNA targeting GRA2 (*TGGT1_227620* gene) constructed from pSAG1::CAS9-U6::sgUPRT<sup>62</sup>, by replacing the UPRT-targeting sgRNA by a sgRNA targeting GRA2: sequence 5'-TTTTCCGGAGTTGTTAACCA, corresponding to sgRNA *TGGT1_227620_5* described in Sidik et al.<sup>63</sup> and the pGRA2/Ble/GRA2 plasmid coding for the bleomycin hydrolase resistance marker flanked by 5' and 3' UTR of GRA2 gene<sup>64</sup>. Selection was done by a 3h pulse with 50 µg/ mL phleomycin followed by subsequent culture with 5 µg/ mL phleomycin final concentration. All tachyzoites were cultured *in vitro* through successive passages on confluent monolayers of human foreskin fibroblasts (HFF) cells using DMEM enriched with 1% FCS (GIBCO). HFF were acquired from ATCC (Hs27 ref # CRL-1634). For mouse infections, infected HFF were scraped, tachyzoites were released through a 23G needle, filtered through a 3 µm polycarbonate hydrophilic filter (it4ip S.A.) and 200 Tg.GRA6-OVA or 1000 Tg.ΔGRA2-GRA6-OVA tachyzoites were injected intra-peritoneally (i.p.) in 200 µl PBS. In mice adoptively transferred with OT-I T cells, *T. gondii* infection was performed one day after the injection of OT-I T cells.

## METHOD DETAILS

### Generation of bone marrow chimeras

Mixed bone marrow chimeras *Id2* TKO (*CD45.2*⁺): WT (*CD45.1*⁺) were generated by transplanting a mixture of wild-type (*CD45.1*⁺) and *Id2*<sup>fl/fl</sup>*CD4*<sup>Cre+</sup> (*CD45.2*⁺) bone marrow (BM) cells at a ratio 1 : 4 and control mixed chimeras were produced using a mixture of BM cells from WT (*CD45.1*⁺) mice and bone marrow cells from *Id2*<sup>fl/+</sup>*CD4*<sup>Cre-</sup> or *Id2*<sup>+/+</sup>*CD4*<sup>Cre+</sup> (noted as WT *CD45.2*⁺) littermates from the *Id2* floxed;*CD4*cre colony at a ratio 1 : 2 to lethally irradiated (800 rads) *CD45.1*⁺ *CD45.2*⁺ (F1) recipient mice. Mice were allowed to reconstitute for 7-8 weeks before infection.

### Isolation and adoptive transfer of OT-I CD8⁺ T cells

TCR transgenic OVA-specific CD8⁺ T cells (OT-I) were isolated from spleen and inguinal lymph nodes (LNs) of TCR transgenic mice by negative selection using the Dynabeads Untouched Mouse CD8 Cells kit (Invitrogen). Naive CD8⁺CD44⁺ T lymphocytes were subsequently isolated using the CD8α T Cell Isolation Kit (Miltenyi biotec) through addition of an anti-CD44 biotinylated antibody (clone IM7, BD pharmingen) to the antibody mix by negative selection using an MS column and MidiMACS separator. CD8⁺ T cells were then cultured at 1.10⁶ cells/well in 12 well/ plate that were coated overnight one day earlier with anti-CD3 mAb (clone145-2C11, BD pharmingen, 5 µg/ml) within 2 ml/well of complete medium (RPMI 1640, 10% FBS (Gibco), 1% 2mM L-glutamine (Life Technologies), 1% HEPES (Life Technologies), 1% non-essential amino acids (Life Technologies), 100U/ml penicillin (Gibco) and 100µg/ml Streptomycin-sulfate (Gibco), 0.05mM βmercaptoethanol (Sigma) supplemented with anti-CD28 mAb (clone 37.51, BD pharmingen, 2 µg/ml) and recombinant human IL-2, mouse IL-7 and IL-15 (5ng/ml) (all from Peprotech) for 3 days. Cells were transduced with retroviruses 24h after activation and 10.10³ cells of FACS-sorted retrotransduced cells were intravenously transferred into recipient mice 3 days later.

### Retroviral transduction of OT-I TCR transgenic T cells

Murine stem cell virus (MSCV)-*Id2*-IRES-GFP, MSCV-IRES-GFP, MSCV-Tcfe2a-IRES-Cherry and MSCV-IRES-Cherry have been previously described<sup>24,51</sup>. OT-I CD8⁺ T cells were enriched from the spleen and inguinal LNs as described above. Retroviral supernatants were then spun for 1 h at 3100g at 4 °C in 12-well-plates coated with 32 µg/ml RetroNectin (Takara). Meanwhile, polybrene (5µg/ml) was added to the cell culture medium. Retrovirus supernatant was then carefully removed from the plate and OT-I T cells were added to retrovirus-coated plate, spun for 10 min at 254 g and cultured with human IL-2, mouse IL-7 and mouse IL-15 (all at 5ng/ml) in complete RPMI for 2 days. For adoptive transfer experiments, 2 days after transduction GFP⁺ or mcherry⁺ cells were
purified by flow cytometric cell sorting (BD FACS Aria™ Fusion) prior to adoptive transfer into recipient mice. Of note, for experiments involving E2A overexpression, OT-I cells expressing a low to intermediate level of mCherry were FACS purified to avoid increased cell death in cells expressing higher level of E2A. Following T cell adoptive transfer recipient mice were then infected the following day with Tg.GRA6-OVA.

### mAb-depleting treatments

To deplete CD4⁺ T cells, an anti-CD4α mAb (rat IgG2b, clone GK1.5, cat # BX-BP0003 from BioXcell) or isotype (rat IgG2b, Clone LTF-2, cat # BP0090 from BioXcell) was injected intraperitoneally at day -3 and day -1 (100 µg per mouse) before infection and once weekly thereafter until the end of the experiment at day 35 post-*T.gondii* infection.

### Isolation of spleen and brain leukocytes

Mice received a lethal dose of ketamine (100 mg/kg) and xylazine (10 mg/kg) and then underwent intracardial perfusion with PBS 1X. Subsequently, spleen and brain were collected. Splenocytes were mashed through a 70 µm cell strainer (Falcon) in complete RPMI (GIBCO) supplemented with 10% FCS (GIBCO) and red blood cells were lysed in ACK. Brains were minced, homogenized, and digested for 45min in digestion solution composed of Hanks' balanced salt solution supplemented with collagenase D (1 mg/ml, Roche Diagnostics cat # 54 11088882001) and deoxyribonuclease (DNase) I (20 µg/mL, Sigma-Aldrich cat # DN25). Cells were passed through a 70 µm cell strainer, which was washed with 5 ml of washing solution (Hank's balanced solution containing 2% FCS and Hepes) and then cells were left to decant 12 minutes in 15 ml Falcon tube. After decantation 13ml out of the 15ml were collected and washed in 50 ml Hank's washing solution and centrifuged 5 min at 607g. Cell pellet was then suspended in 30% Percoll (GE Healthcare) and centrifuged at 1590g for 30 minutes without brake. The pelleted cells were resuspended in FACS buffer (PBS 1X, 2% FCS), washed 2 times and utilized for subsequent experiments.

### Flow cytometry

To identify OVA-derived SIINFEKL peptide specific-CD8⁺ T cells, splenocytes and brain leukocytes were incubated with PE-coupled SIINFEKL-loaded H-2 Kᵇ dextramers (Immunex, dilution 1:50) in complete RPMI during 45 min at room temperature. Then, cells were stained with Fc receptor blocking antibodies (CD16/32, clone 93, dilution 1:5). Specific cell-surface staining was performed using a standard procedure with fluorochrome-labeled antibodies against CD8a, CD3e, CD45.1, CD45.2, Slamf6, Tim3, PD-1, CD69, CD103, CD49a, CD62L and CD44. Cells were then labelled with eFluor 780 Fixable Viability Dye (eBioscience, dilution1/2000). For intracellular staining, Granzyme B, IFN-γ and TNF were detected using Cytofix/Cytoperm kit (BD Biosciences) while Tox staining were performed using Foxp3/Transcription Factor Staining Buffer Set (eBioscience) following the manufacturer's protocol. Analysis was performed on a FACS LSR Fortessa (BD Biosciences) and data were analyzed using FlowJo flow cytometry analysis software version 10.9.0. For analysis of phenotypic markers, mice with less than 20 events in the relevant gate were excluded from the analysis.

### In vitro generation of exhausted CD8⁺ T cells

Protocol was adapted from ⁴². Briefly, CD8⁺ T cells were purified from spleens and inguinal LNs of OT-I mice by negative selection with magnetic beads. In each well of a 24-well plate, 5x10⁵ of the purified CD8⁺ T cells were cultured in complete RPMI medium supplemented with IL-15 (5ng/ml, Peprotech, Cat 210-15) and IL-7 (5ng/ml, Peprotech, Cat 210-07) with 10ng/ml OVA peptide. For single peptide stimulation, cells were cultured in the presence of OVA peptide for 48h hours. The peptide was then removed by washing the cells two times with complete medium on day 2. For the remaining 5 days, the cells were cultured in the complete medium with cytokines. For repeated peptide stimulation, 10ng/ml OVA peptide was added daily for 7 days. To ensure comparable culture conditions, the cells were washed on day 2, similar to the procedure used for single peptide stimulation. When the cells reached maximum density, they were split and cultured with fresh complete medium containing cytokines.

### T cell restimulation for intracellular cytokine assessment

For ex vivo stimulation one third of Percoll-isolated brain leukocytes were incubated for 4h at 37°C with Phorbol 12-Myristate 13-Acetate (PMA) (50 ng/ml) and ionomycin (1000 ng/ml) (Sigma-Aldrich) in presence of monensin (Golgestop) (dilution 1/1428 from BD Biosciences). For in vitro exhaustion experiments, 5.10⁵–8.10⁵ OT-I CD8⁺ T cells were incubated for 4h at 37°C with 10µg/ml of OVA peptide in presence of monensin (Golgestop) (1/1428) (BD Biosciences).

### In vitro generation of Trm-like CD8⁺ T cell

OT-I CD8⁺ T cells were isolated from the spleen and inguinal LNs and activated as described above (Isolation and adoptive transfer of OT-I CD8⁺ T cells). Cells were cultured in the presence of IL-2 (5 ng/ml), IL-7 (5 ng/ml), and IL-15 (5 ng/ml), (all from Peprotech), to support activation and proliferation. After 24 hours of activation, cells were transduced with retroviral vectors encoding either control-IRES-mCherry or E2A-IRES-mCherry as described above. Transduced cells were then maintained in culture with IL-2, IL-7, and IL-15. On day 5 post-activation, the culture medium was supplemented with TGF-β (5 ng/ml), IL-12 (5 ng/ml), and IL-33 (5 ng/ml) to promote the differentiation of Trm-like CD8⁺ T cells⁴⁶. On day 7, cells were harvested and analyzed by flow cytometry to assess the expression of Trm markers CD69 and CXCR6.
## Parasite load analysis

Parasite DNA quantification by qPCR was conducted on genomic DNA extracted from 5% of every brain homogenate using the DNEasy Blood & Tissue Kit (QIAGEN). As previously outlined⁶⁵, amplification of a 529-bp repeat element in the *T. gondii* genome was achieved using the TOX 9 and TOX 11 primers. The quantity of parasite genomes per mg of tissue DNA was determined by comparing it with a standard curve, which was generated using a known quantity of Pru tachyzoites. The Primers sequences were:

*   TOX 9: 5' -AGGAGAGATATCAGGACTGTAG
*   TOX 11: 5' -GCGTCGTCTCGTCTAGATCG

## Single cell RNA-seq libraries

scRNA-seq dataset is from one experiment in which C57BL/6 mice were chronically infected with Tg.GRA6-OVA and analyzed at day 154pi. CD8⁺ T cells were isolated from pooled spleens or brains of 4 infected mice. CD8⁺ T cells were purified using MACS Miltenyi mouse CD8α T Cell Isolation kit (Miltenyi Biotec 130-104-075) before proceeding to single-cell emulsion with 15946 splenic CD8⁺ T cells and 11856 brain CD8⁺ T cells, respectively. Single-cell libraries were generated with Chromium Next GEM Single Cell 5' Kit v2 according to the manufacturer's protocol (10X Genomics). Library size and quality were verified on a Fragment Analyzer (Agilent). Libraries were sequenced on 1 lane of SP flowcell with Illumina NovaSeq6000 sequencer, using paired-end sequencing (2 x 150) and a single 8 bp-long index.

## Bioinformatical analysis of single-cell RNA-seq data

### Single-cell RNA sequencing data analysis

Single-cell RNA-seq data were sequenced and profiled using the Chromium 10X technology. Fastq files processing was carried out with CellRanger 10X software (version 4.0.0)⁶⁶ and reads were mapped against mouse reference genome (version mm10-2020-A). Filtered barcode matrix generated from CellRanger was then loaded into R (version 4.0.3) (R Core Team. R Foundation for Statistical Computing, 2022) and used as input for Seurat R package (version 4.2.1)⁶⁷. Multiple filters were applied to keep cells of interest: first filter to exclude low-quality, dying cells and doublets given sample-specific thresholds on feature, UMI and mitochondrial transcript count per cell. Second filter aims to remove non lymphoid cells based on cell cluster marker genes, and cell type identification with clustifyR R library (version 1.10.0). Data were processed following the standard Seurat pipeline: gene were normalized and scaled with NormalizeData and ScaleData Seurat function, highly variable genes were selected with FindVariableFeatures function, we then reduced the dimensionality of our data by PCA and clustered our cells using FindNeighbors, FindClusters, RunUMAP Seurat functions. We identified differentially expressed genes for cluster and sample with FindAllMarkers and FindMarkers function. Functional enrichment analysis was performed with fgsea package⁶⁸ (v1.24.0) or the GSEA software⁶⁹ (http://www.broad.mit.edu/gsea/) with published gene signatures¹⁰,²⁴,³⁴.

## QUANTIFICATION AND STATISTICAL ANALYSIS

Statistical analyses for all experiments were performed with Prism software v10.1.2 (GraphPad). The normality of all datasets was evaluated using Shapiro test. If the data were normally distributed two-tailed unpaired t-test (with or without Welsh correction depending on equal variance tests) or paired t-tests were conducted. If the data were not normally distributed, non-parametric tests (Mann-Whitney test or Wilcoxon matched-pairs signed rank) were utilized. Tests were corrected for multiple comparisons when applicable using two-stage step-up method of Benjamini, Krieger and Yekutieli. *P* values ≤0.05 were considered statistically significant and are indicated on the figures as follows: *P* < 0.05, **P** < 0.01, ***P** < 0.001, and ****P** < 0.0001.