Immune targeting and host-protective effects of the latent stage of Toxoplasma gondii

Eberhard, Julia N.; Shallberg, Lindsey A.; Winn, Aaron; Chandrasekaran, Sambamurthy; Giuliano, Christopher J.; Merritt, Emily F.; Willis, Elinor; Konradt, Christoph; Christian, David A.; Aldridge, Daniel L.; Bunkofske, Molly E.; Jacquet, Maxime; Dzierszinski, Florence; Katifori, Eleni; Lourido, Sebastian; Koshy, Anita A.; Hunter, Christopher A.

doi:10.1038/s41564-025-01967-z

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Published: 27 March 2025

Immune targeting and host-protective effects of the latent stage of Toxoplasma gondii

Nature Microbiology volume 10, pages 992–1005 (2025)Cite this article

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Abstract

Latency is a microbial strategy for persistence. For Toxoplasma gondii the bradyzoite stage forms long-lived cysts critical for transmission, and its presence in neurons is considered important for immune evasion. However, the extent to which cyst formation escapes immune pressure and mediates persistence remained unclear. Here we developed a mathematical model highlighting that bradyzoite-directed immunity contributes to control of cyst numbers. In vivo studies demonstrated that transgenic CD8⁺ T cells recognized a cyst-derived antigen, and neuronal STAT1 signalling promoted cyst control in mice. Modelling and experiments with parasites unable to form bradyzoites (Δbfd1) revealed that the absence of cyst formation in the central nervous system did not prevent long-term persistence but resulted in increased tachyzoite replication with associated tissue damage and mortality. These findings suggest the latent form of T. gondii is under immune pressure, mitigates infection-induced damage and promotes survival of host and parasite.

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Main

Many infections lead to an asymptomatic state with low levels of micro-organism persistence despite generation of protective immunity. For some, persistence is linked to transition from a lytic to a non-lytic quiescent state that can be difficult to treat. These latent forms are considered an evolutionarily conserved strategy for immune evasion, while reactivation can cause disease and enhanced transmission,^1,2,3,4,5,6 but a lack of models has limited the ability to test how latency impacts persistence^7,8. For the parasite Toxoplasma gondii, the highly replicative tachyzoite transforms to the slow-growing bradyzoite which forms long-lived cysts predominantly in neurons^4,9,10,11. This switch is mediated by the transcription factor BFD1 and the RNA binding protein BFD2^12,13,14. The cyst stage facilitates oral transmission and is considered important for immune evasion: two features that contribute to the evolutionary success of T. gondii¹⁵.

T. gondii provides a model of natural host–pathogen interactions in mice, and the parasite’s genetic tractability allows studies to dissect immune resistance to this organism^16,17. Acute infection is dominated by dissemination of tachyzoites which replicate in many cell types, causing extensive tissue damage. With the onset of protective immunity dominated by T-cell production of IFNγ, the chronic phase is characterized by cyst formation in the central nervous system (CNS)^10,11. While cysts had been considered dormant and the cyst wall impermeable, their relationship with the host cell is dynamic^18,19,20. Cyst burden and size change over time, and periodic reactivation which releases tachyzoites can contribute to recrudescence and cause disease in patients with immune deficiencies that affect T cells^11,21,22,23. Resistance to T. gondii is marked by a balance between limiting tissue damage from tachyzoite replication and immune pathology associated with this infection^{24,25,26,27,28,29}.

Many features of the brain contribute to its immune-privileged status^30,31. Neurons are major histocompatibility complex (MHC) class I^low and show reduced responsiveness to IFNγ, which may underlie their ability to shelter pathogens^31,32,33,34. This perspective is challenged by reports that CD8⁺ T cells can kill virally infected neurons and evidence of non-cytopathic IFNγ-mediated mechanisms of viral clearance^{35,36,37,38,39}. Previous reports suggested that IFNγ did not control T. gondii in neurons⁴⁰, but extended incubation of neurons with IFNγ does limit tachyzoite growth³⁴. While T-cell production of IFNγ mediates resistance to T. gondii⁴¹, there is also evidence that CD8⁺ T cells can recognize tachyzoite-infected neurons^42,43 and that cytotoxicity contributes to CNS parasite control^44,45. Whether cysts are directly targeted by CD8⁺ T cells is unknown, but microglia and CD8⁺ T cells can interact with the cyst stage^{46,47,48,49,50}. In mice, CNS cyst burden peaks during weeks 3–5 of infection, followed by a decline in cyst numbers^18,21,51,52. Whether cyst reactivation allows the immune response to eliminate tachyzoites and limit formation of new cysts or there is a direct mechanism to eliminate bradyzoites is unclear.

The ability to quantify T-cell responses and changes in parasite burden during toxoplasmosis has formed the basis for mathematical models describing different facets of this infection^53,54,55,56. No existing model accounts for the possibility of immune-mediated cyst removal. In this Article, ordinary differential equations (ODEs) were developed to understand how the immune response to different developmental stages of T. gondii might influence parasite burden in the CNS. This model suggested immune responses targeting tachyzoites and bradyzoites lead to cyclic parasite growth and control, and inclusion of cyst lysis and reactivation dampens these oscillations. For most realistically small values of the cyst lysis rate, cyst immune clearance is necessary to produce the experimentally observed rise and fall in cyst numbers. To test the predicted roles of cyst formation and cyst-directed immunity, transgenic parasites with stage-specific expression of the model antigen OVA, parasites unable to form cysts, and mice with blunted neuronal IFNγ signalling were used. These studies revealed a CD8⁺ T-cell response against the latent form of T. gondii and that the cyst provides a replicative sink required to mitigate tissue damage, thereby promoting survival of host and parasite.

Results

Modelling stage-specific immunity to T. gondii in the CNS

A model was developed to investigate the relationship in the CNS between tachyzoite replication, cyst formation, reactivation and immunity. These relationships are represented with populations shown as circles and reactions as squares (Fig. 1a). The corresponding system of ODEs is given in equations (1)–(3).

$$\frac{{\rm{d}}{{{I}_{\rm{T}}}}}{{\rm{d}}{{t}}}={\beta }_{\rm{T}}{I}_{\rm{T}}+{\beta }_{\rm{B}}{I}_{\rm{B}}-{d}_{\rm{T}}{I}_{\rm{T}}-{\psi }_{\rm{T}}\frac{{I}_{\rm{T}}Z}{{S}_{0}}-{c}_{\rm{TB}}{I}_{\rm{T}}$$

(1)

$$\frac{{\rm{d}}{I}_{\rm{B}}}{{\rm{d}}t}=-{d}_{\rm{B}}{I}_{\rm{B}}-{\psi }_{\rm{B}}\frac{{I}_{\rm{B}}Z}{{S}_{0}}+{c}_{\rm{TB}}{I}_{\rm{T}}$$

(2)

$$\frac{{\rm{d}}Z}{{\rm{d}}t}={a}_{\rm{T}}\frac{{I}_{\rm{T}}Z}{{S}_{0}}+{a}_{\rm{B}}\frac{{I}_{\rm{B}}Z}{{S}_{0}}-\mu Z$$

(3)

**Fig. 1: Compartmental modelling of *T. gondii* infection in the CNS predicts the presence of immune responses to tachyzoites and bradyzoites.**

Detailed derivation of the ODEs, explanation of rate constants and comparison to the previous model are provided (Supplementary Text Section 1). The approach is similar to that in ref. ⁵³ but considers the possibility of immune pressure on bradyzoites. The numbers of tachyzoite-infected cells, bradyzoite-infected cells and immune cells are denoted I_T, I_B and Z, respectively. The number of infected cells remains much less than the total number of cells in the CNS, so it is assumed the uninfected cell number S₀ remains constant. I_T increases at a rate β_TI_T, while tachyzoite to bradyzoite differentiation occurs at a rate c_TBI_T. Bradyzoite to tachyzoite reactivation occurs at a rate β_BI_B. Cells infected with tachyzoites or bradyzoites may rupture (at a rate d_TI_T or d_BI_B) or be cleared by immune cells (at a rate ψ_TI_TZ/S₀ or ψ_BI_BZ/S₀). Tachyzoite- or bradyzoite-infected cells trigger the immune response at a rate a_TI_TZ/S₀ or a_BI_BZ/S₀. Feedback between the immune response and infection mirrors a predator–prey interaction: without immune pressure, parasite growth is unrestricted, but when immune cells are present, they limit parasite replication. Immune cell death occurs at a rate µZ. In Fig. 1a, the two arrows from β_T to I_T represent a +1 increase in parasite numbers, and similarly, two arrows are used to represent the ability of infected cells (a_T/a_B) to amplify the immune response (Z).

Equations (1)–(3) were solved to demonstrate the expected infection dynamics resulting from the presence or absence of cyst lysis and cyst immune clearance. Model parameters were estimated based on the literature^{18,21,57,58,59,60,61,62,63,64,65,66,67} and our experimental data (Supplementary Text Section 4 and Supplementary Table 1). Setting certain parameters to zero illustrates several key scenarios (Fig. 1b). When the immune response is disabled (top row), numbers of tachyzoite-infected cells grow exponentially, even if bradyzoite differentiation and reactivation are incorporated (Supplementary Text Section 2). The inclusion of only anti-tachyzoite immune responses (ψ_T; second row) results in the initial exponential growth of infected cells that triggers recruitment of immune cells, then a subsequent reduction in infected cells and contraction of the immune response. This is followed by cycles of tachyzoite recrudescence and control, apparent as oscillations in tachyzoite-infected cell number (Supplementary Text Section 3.1). Inclusion of bradyzoite differentiation without reactivation (middle panel) predicts a stepped increase in bradyzoite numbers with each reactivation event. The inclusion of bradyzoite differentiation and reactivation without anti-cyst immune responses results in monotonic growth of cysts (right-hand panel). Increasing d_B leads to a rise and fall in cyst numbers, although this is only observed for a small range of biologically relevant values (Supplementary Text Section 3.2).

In the final simulations (bottom row), tachyzoite- and bradyzoite-specific immune responses are incorporated. Inclusion of differentiation without reactivation (bottom middle panel) results in oscillations in infected cell number which increase in magnitude with time (Supplementary Text Section 3.3). When bradyzoite differentiation and reactivation are integrated, dampened oscillations in infected cell number are found (bottom right-hand panel). While rupture and immune clearance can cause a decline in cyst numbers, rupture leads to a steady value of cysts, whereas immune clearance leads to a decline in cyst numbers followed by oscillations in cyst populations.

This model implies that differentiation and reactivation are necessary to dampen oscillations in infected cell number and immune cell infiltration, and incorporation of a small bradyzoite immune response markedly reduces the number of infected cells (Supplementary Text Section 5.2). These models illustrate that to recapitulate qualitative features of this infection (a rise then fall in the number of tachyzoite- and bradyzoite-infected cells), one must understand the interaction between bradyzoites and the immune system. Below we provide evidence consistent with a_B and ψ_B > 0 by demonstrating that CD8⁺ T cells and IFNγ are activated by and exert pressure on bradyzoite-infected cells.

Cyst-derived antigen induces a CD8⁺ T-cell response

To determine whether CD8⁺ T cells recognize cyst-derived antigens, parasites were generated expressing the model antigen OVA under a bradyzoite-specific promoter (bag1-OVA), and these were compared to parasites expressing OVA in tachyzoites and bradyzoites⁶⁸ (tub1-OVA; Fig. 2a). The transfer of OT-I T cells (transgenic CD8⁺ T cells that recognize the SIINFEKL epitope of OVA) allowed a comparison of the ability of these strains to activate CD8⁺ T cells. Microscopy with bag1-OVA parasites confirmed cyst-specific expression of OVA (Extended Data Fig. 1a). During acute infection, these strains established comparable parasite burdens and endogenous parasite-specific CD4⁺ and CD8⁺ T-cell responses (Extended Data Fig. 1b,c), but only tub1-OVA induced endogenous SIINFEKL-specific T cells (Extended Data Fig. 1b). Infection was also induced 1 day after transfer of congenically distinct CD45.1⁺CD45.2⁺ OT-I T cells that express Nur77^GFP upon T-cell receptor (TCR) engagement (Extended Data Fig. 1d,e)⁴⁸. OT-I T cells expanded and were present in the brain and spleen at 14 days post-infection (d.p.i.) with tub1-OVA, but not bag1-OVA. At 28 d.p.i., when cyst formation occurs in the CNS, both infections resulted in OT-I T cells in the brain (Extended Data Fig. 1f). A subset of these cells were Nur77^GFP+ (Extended Data Fig. 1g). The OT-I T-cell response in the CNS was approximately 50-fold greater during tub1-OVA infection than bag1-OVA infection (Extended Data Fig. 1f). This difference could reflect altered priming due to delayed OVA expression in bag1-OVA parasites. To normalize for time of priming, OT-I T cells were transferred into mice at 21 d.p.i. (when both parasite strains are expected to express OVA) and analysed 2–3 weeks later (Fig. 2b). The OT-I T-cell response induced by bag1-OVA remained lower in magnitude and showed a lower frequency of Nur77^GFP+ cells (Fig. 2c,d). These data suggest that priming kinetics do not account for differences in magnitude of the OT-I T-cell response or levels of TCR engagement between tub1-OVA and bag1-OVA parasites.

We next compared OT-I T cells in the CNS responding to tub1-OVA or bag1-OVA parasites using Uniform Manifold Approximation and Projection (UMAP) analysis. This approach revealed seven clusters with varied expression of effector T-cell markers (KLRG1, CX3CR1, T-bet), inhibitory receptors (PD-1) and tissue residency markers (CD69, CD103) (Fig. 2e–g). OT-I T cells responding to tub1-OVA showed heterogenous effector phenotypes with KLRG1⁺CX3CR1⁺, KLRG1⁺CX3CR1⁻ and KLRG1⁻CX3CR1⁻ populations that were T-bet^hi (Fig. 2h,i). A small subset were CD69⁺CD103⁺ or PD-1^hi (Fig. 2j,k). By contrast, OT-I T cells responding to bag1-OVA were dominated by a KLRG1⁻CX3CR1⁻ population with decreased T-bet expression. These cells also co-expressed tissue resident memory markers (CD69⁺CD103⁺) and high levels of PD-1 (Fig. 2h–k). When OT-I T cells from infected brains were stimulated with the SIINFEKL peptide, there were similar levels of degranulation (a measure of cytotoxic potential), but those responding to bag1-OVA had reduced IFNγ production (Fig. 2l,m). These results reveal a sub-population of CD8⁺ T cells induced and maintained by cyst-derived antigen with a distinct phenotype and reduced effector capacity.

Neuronal STAT1 mediates cyst control

The cytokine IFNγ signals through STAT1 to mediate resistance to T. gondii^41,69, and deletion of Stat1 in microglia or astrocytes results in increased parasite replication and immune infiltration in the CNS^70,71. To test the role of IFNγ in controlling T. gondii in neurons, Snap25^Cre-Stat1^flox/flox mice (Stat1^ΔNEU) with blunted neuronal IFNγ signalling were infected. At 20 d.p.i., before extensive cyst formation, wild-type (WT) and Stat1^ΔNEU mice showed no difference in total parasite burden or numbers of infected leukocytes in the CNS (Fig. 3a,b). At 3 months post-infection (m.p.i.), parasite burden remained comparable between WT and Stat1^ΔNEU mice (Fig. 3c), but cysts in Stat1^ΔNEU brains were larger (indicative of longevity) and more numerous (Fig. 3d–f). This elevated cyst burden was not associated with increased mortality (Fig. 3g), and there were no signs of increased tachyzoite replication or associated tissue pathology (Fig. 3h,i). There were also no alterations in the numbers or phenotype of parasite-specific CD8⁺ T cells in the CNS (Extended Data Fig. 2a–f). These results indicate that neuronal STAT1 underlies a mechanism of cyst control in vivo, consistent with ψ_B > 0 in our model.

Cyst formation is not required for parasite persistence

While inclusion of tachyzoite-to-bradyzoite conversion in the model produced infection dynamics that mirrored natural infection (Fig. 1), the inability to form bradyzoites (c_TB = 0) produced increased numbers of tachyzoite-infected cells early after parasite invasion of the CNS (Fig. 4a). In this scenario, parasite numbers were controlled as infection progressed; however, even in the absence of cyst formation, tachyzoites persisted and underwent periodic recrudescence as immunity waned (Fig. 4b). To test this experimentally, tub1-OVA parasites lacking BFD1 (Δbfd1), a master regulator of tachyzoite to bradyzoite transition¹², were generated. At 14 d.p.i., mice infected with WT or Δbfd1 parasites had comparable parasite burden, splenic T-cell responses and serum IFNγ levels (Extended Data Fig. 3a–c). However, higher levels of tachyzoite-infected cells were present in the brains of Δbfd1-infected mice at 14 and 21 d.p.i., followed by a contraction from 30 to 45 d.p.i. and in this experiment a recrudescence at 60 d.p.i. (Fig. 4c). The cyst wall binding reagent dolichos biflorus agglutinin (DBA⁺) was readily detected on parasitophorous vacuoles in WT-infected mice, whereas most parasitophorous vacuoles in Δbfd1-infected mice were DBA⁻ (Fig. 4d,e). The fraction of DBA⁺ Δbfd1 parasitophorous vacuoles showed weaker DBA staining than WT parasitophorous vacuoles, and Δbfd1 parasites within these DBA^low vacuoles were Sag1⁺ (a tachyzoite surface antigen) and SRS9⁻ (a bradyzoite surface antigen). Conversely, WT parasites within DBA⁺ vacuoles were Sag1⁻SRS9⁺ (Extended Data Fig. 3d). Thus, Δbfd1 parasites do not form cysts in the brain.

**Fig. 4: Latent stage conversion is not necessary for chronic infection.**

To determine whether cyst formation is required for parasite persistence, the brains of surviving WT- and Δbfd1-infected mice were examined at 6 m.p.i. WT-infected mice exhibited encephalitis, obvious cysts and quantifiable parasite burden (Fig. 4f,g). By contrast, Δbfd1-infected mice lacked overt signs of inflammation or parasite replication, although low parasite burden was detectable (Fig. 4f,g). Treatment of survivors with anti-IFNγ resulted in increased parasite burden in the brains of WT- and Δbfd1-infected mice at 6 m.p.i., associated with enhanced parasite replication. (Fig. 4f,g). Thus, cyst formation maintains a higher parasite burden in the CNS, but it is not essential for long-term persistence of T. gondii.

Cyst formation is host protective

While WT- and Δbfd1-infected mice had similar initial rates of survival, Δbfd1-infected mice showed increased mortality at 20–40 d.p.i. (Fig. 5a). Treatment of these mice with sulfadiazine (which inhibits tachyzoite replication) starting at 21 d.p.i. enhanced survival (Fig. 5a). Histopathological assessment of Δbfd1-infected brains at 30 d.p.i. showed areas of severe tissue necrosis surrounding foci of tachyzoite replication (Fig. 5b,c). By contrast, WT-infected brains, despite the presence of inflammation and gliosis, did not show necrosis or remarkable tissue damage (Fig. 5b,c). Differences in additional indicators of CNS pathology were also apparent in WT- and Δbfd1-infected brains (Extended Data Fig. 4a,b). These data indicate that higher mortality during Δbfd1 infection is associated with enhanced levels of tachyzoite replication.

**Fig. 5: *Δbfd1* infected mice die of tachyzoite replication despite a competent immune response.**

One explanation for increased CNS tachyzoite replication during Δbfd1 infection could be a reduced local immune response. However, Δbfd1-infected mice had increased CNS immune infiltration at 20–45 d.p.i. compared to WT-infected mice (Fig. 5d and Extended Data Fig. 4c). By 60 d.p.i., immune infiltration was similar between groups (Fig. 5d). Comparison of immune infiltrates at 30 d.p.i. revealed a similar composition between WT and Δbfd1 infection (Fig. 5e,f and Extended Data Fig. 4d). The only difference was an increase in the population of inflammatory monocytes during Δbfd1 infection (Fig. 5f–h). Phenotypic analysis was also performed after transfer of OT-I T cells 1 day before infection with WT or Δbfd1 parasites constitutively expressing OVA. At 14 and 30 d.p.i. OT-I T cells in the brain were phenotypically similar between infections (Extended Data Fig. 4e), although at 30 d.p.i. with Δbfd1 parasites there were reductions in CD69⁺CD103⁺ and KLRG1⁻CX3CR1⁻ memory-like populations (Extended Data Fig. 4f,g). These results suggest that despite a competent immune response in the CNS, increased tachyzoite replication in the brain during Δbfd1 infection leads to host mortality. In additional studies with BALB/c mice, which are resistant to toxoplasmic encephalitis^72,73, Δbfd1-infected mice showed increased CNS immune infiltration, neuropathology and necrosis but not increased mortality or total parasite burden (Extended Data Fig. 5a–f). A recent study also showed that CBA mice infected with a cyst-defective type III strain of T. gondii had higher tachyzoite burdens that were capable of reactivation at 5 m.p.i. (ref. ¹⁴). These studies highlight that across toxoplasmic encephalitis models, abrogation of cyst formation is associated with increased tachyzoite replication and CNS pathology.

Discussion

While neurons represent a refuge from the immune response for many pathogens, neurons infected with viruses or T. gondii tachyzoites can be recognized by CD8⁺ T cells^35,42,74. However, the role of CD8⁺ T cells in controlling the latent stage of T. gondii is less understood. There are reports that depletion of CD8⁺ T cells in chronically infected mice does not impact cyst numbers⁷⁵, whereas others have shown that perforin-deficient mice have increased cyst numbers⁴⁴. In addition, in severe combined immunodeficiency (SCID) mice the transfer of CD8⁺ T cells from infected mice led to a perforin-dependent reduction in cyst numbers^45,50. Nevertheless, it is unclear whether CD8⁺ T-cell-mediated reduction of cysts is due to tachyzoite control or lysis of cyst-infected neurons. Intravital imaging has revealed CD8⁺ T cells arrested near cysts, but direct interactions with and lysis of bradyzoite-infected neurons have not been observed^46,47,48,55. Here, we demonstrate through (1) generation of CD8⁺ T-cell responses against cyst-derived antigen and (2) increased cyst burden with ablation of neuronal STAT1 that there is immune-mediated recognition and control of T. gondii cysts. These findings, combined with modelling of host–parasite dynamics, suggest that tachyzoite clearance and bradyzoite-directed immune pressure are required to produce the progressive reduction in cyst numbers typical for this infection^21,51.

These studies are currently unable to distinguish whether there are T-cell responses primed against tachyzoites that can respond to antigens also expressed by bradyzoites⁷⁶, but nevertheless our findings raise questions about the mechanisms underlying CD8⁺ T-cell recognition of cyst antigens. The ability of neurons to upregulate MHC class I might allow infected neurons to present cyst-derived antigen to CD8⁺ T cells. Alternatively, reactivation could release cyst-derived antigens for cross-presentation by local microglia or dendritic cells. We favour a model analogous to some viral systems where local T-cell activation and production of IFNγ provides sustained signals to help neurons control infection^36,38,39,77. Non-cytopathic IFNγ-mediated control may explain the presence of neurons that had previously been infected with T. gondii but cleared the parasite⁷⁸. Many IFNγ-mediated anti-microbial mechanisms contribute to the control of tachyzoites⁷⁹, and the immunity-related GTPases have been implicated in the ability of a subset of neurons to clear T. gondii³⁴, but the relevance of these mechanisms to bradyzoite control is uncertain.

This study focused on the mechanisms involved in cyst control, but the persistence of cysts despite immune pressure suggests that this stage can mitigate immune effector responses. Consistent with this idea is bradyzoite production of the STAT1 antagonist TgIST^80,81,82, which suggests this stage is under selective pressure from IFNγ. In addition, the CD8⁺ T-cell responses to cyst-derived antigen from bag1-OVA parasites comprised an unanticipated, phenotypically distinct sub-population of CD69⁺CD103⁺PD1^hi cells with a reduced ability to produce IFNγ. Other studies on CD8⁺ T cells during toxoplasmic encephalitis have identified a T_rm-like (CD69⁺CD103⁺) subset and shown expression of PD-1 (refs. ^43,46,71,83), which limits T-cell activation and production of IFNγ⁸⁴. Because neurons express low levels of MHC class I, lack costimulatory molecules and express PD-L1 (refs. ^85,86), it is possible that CD8⁺ T-cell interactions with infected neurons lead to sub-optimal T-cell responses which could underlie the attrition, but incomplete elimination, of cysts.

The use of ODE models to understand host–pathogen dynamics provides an opportunity to manipulate aspects of host–parasite interactions in ways that are not always accessible through experimentation^87,88. The lack of tractable models has made it hard to test how latency impacts other pathogens⁷, but the computational approaches described here can be adapted to incorporate strain or pathogen-specific features associated with T. gondii or other infections. For example, differences in the rate of cyst formation or ability of different stages to evade the immune response can be accounted for by adjusting model parameters (c_TB) or (ψ_T or ψ_B). ODE models have limitations (Supplementary Text Section 6), and neglecting stochastic effects fails to predict the variety of possibilities with small infected cell numbers. Likewise, cyst reactivation is asynchronous in vivo, and these models do not reflect differences in spatially distinct regions when recrudescence occurs. Implementation of agent-based computational models⁵⁶ could address these issues and provide more granular insights into the contributions of different immune cell populations to CNS infection dynamics. Nevertheless, the combination of modelling and in vivo experiments in this study provides insight into the interplay between the latent stage of T. gondii and host immune responses. Cyst development provides a replicative sink that tempers tachyzoite expansion in the CNS and prevents damage to the host, illustrating the concept that avirulence is a key feature of the parasitic lifestyle^89,90,91. Thus, T. gondii cyst formation represents a trade-off between quiescence, which limits parasite replication, and delayed differentiation, which risks damage to the host.

Methods

Mice

Mice were housed in the University of Pennsylvania Department of Pathobiology vivarium according to institutional guidelines with 12 h light/dark cycles, ambient temperature ranging from 20 °C to 25 °C and ambient humidity ranging from 35% to 55%. C57BL/6J (stock number 000664, RRID:IMSR_JAX:000664), CD45.1 (B6.SJL-Ptprc^a Pepc^b/BoyJ, stock number 002014, RRID:IMSR_JAX:000664), Nur77^GFP (stock number 016617, RRID:IMSR_JAX:016617), OT-I (stock number 003831, RRID:IMSR_JAX:003831) and BALB/c (stock number 000651, RRID:IMSR_JAX:000651) mice were purchased from Jackson Laboratories and bred at the University of Pennsylvania. Snap25^Cre mice were generously provided by H. Zeng at the Allen Institute for Brain Science, and Stat1^flox/flox mice were generously provided by L. Hennighausen at the National Institutes of Health⁹². Snap25^Cre mice were bred with Stat1^flox/flox mice at the University of Pennsylvania to generate Snap25^Cre-Stat1^flox/flox (Stat1^ΔNEU) progeny. Cohorts of male mice were used for all studies, and all mice are on a C57BL/6 background unless otherwise noted. Ethical oversight of all animal studies was approved by the University of Pennsylvania Institutional Care and Use Committee (protocol 805045.)

Infections and T-cell transfers

T. gondii parasites were maintained in culture in human foreskin fibroblasts (HFFs). HFFs were purchased from American Type Culture Collection and were periodically tested for mycoplasma contamination using the MycoScope PCR Mycoplasma Detection Kit (Genlantis, catalogue number MY01050.) To isolate tachyzoites for infection, T. gondii-infected HFFs were gently scraped from flasks, passed 5 times through a 26G syringe and washed with PBS. Mice were infected at 8 weeks of age by intraperitoneal injection with 5,000 tachyzoite parasites grown in vitro.

For OT-I T-cell transfers, whole splenocytes from Naive Nur77^GFP CD45.1⁺CD45.2⁺ OT-I mice were processed as described below. The fraction of OT-I cells in the splenocytes was determined by flow cytometry, and 5,000 OT-I cells were transferred intravenously into mice at the indicated time point before or after infection.

IFNγ blockade and sulfadiazine treatment

In vivo blockade of IFNγ signalling was performed by intraperitoneal injection of 200 μg per dose of rat IgG1 anti-IFNγ (clone XMG1.2, BioXcell) or IgG1 anti-horseradish peroxidase for control mice (HRPN, BioXcell). Injections were administered 2 times per week for 4 weeks before collection and analyses for parasite burden.

Where indicated, mice were treated with the anti-parasitic drug sulfadiazine (Sigma-Aldrich, S8626-25G) via drinking water. Sulfadiazine was reconstituted in dimethylsulfoxide to 50 mg ml⁻¹ and added to drinking water at a final concentration of 0.25 mg ml⁻¹. Sulfadiazine-treated water was administered starting at 21 d.p.i. and refreshed every 3 days for 4 weeks.

Tissue processing and cell counting

To generate single-cell suspensions for flow cytometry, spleens were passed through a 40 μm filter, and red blood cells were lysed for 3 min at room temperature in ammonium-chloride-potassium (ACK) lysis buffer. Brains were diced into 1 mm pieces and digested at 37 °C and 5% CO₂ for 1.5 h with 250 μg ml⁻¹ collagenase/dispase and 10 μg ml⁻¹ DNase and then passed through a 70 μm filter. Leukocytes were then isolated through a 30% and 60% percoll gradient and density centrifugation at 900 g for 25 min. Whole blood was collected through submandibular bleed into 0.05 mM EDTA in PBS. Cells were pelleted, and red blood cells were lysed for 3 min at room temperature in ACK lysis buffer.

For quantification of cellularity and live leukocytes isolated from tissues, a fraction of processed cell suspensions was stained with Guava ViaCount Reagent (catalogue number 11-25209, 240 ml) and analysed on a Guava easyCyte flow cytometer according to manufacturer’s protocol.

Generation of transgenic parasites

To generate Δbfd1 parasites, Pru-tub1-OVA-tdTomato parasites⁶⁸ were mechanically lysed from host cells by scraping and syringe releasing through a 27G needle. Parasites were pelleted for 10 min at 1,000 g, resuspended in Cytomix (10 mM KPO₄, 120 mM KCl, 150 mM CaCl₂, 5 mM MgCl₂, 25 mM HEPES, 2 mM EDTA) and combined with a DNA transfection mixture to a final volume of 400 μl. The final transfection mixture was supplemented with 2 mM ATP and 5 mM glutathione. Two guide RNAs contained on the Cas9-expressing pU6-Universal⁹³ (Addgene 52694) plasmid (Supplementary Data 1) were transfected to target the regions immediately upstream and downstream of the BFD1 locus as previously described¹². A pTUB-mNeonGreen repair template with homology arms matching the 40 bp regions flanking the cut sites was transfected to allow for sorting of ∆bfd1 parasites by fluorescence-activated cell sorting (FACS). After sorting, parasites were plated at limiting dilutions to allow for screening of clonal parasites. A ∆bfd1 clone was confirmed by PCR and sanger sequencing (Supplementary Data 1). However, despite these parasites being mNeonGreen positive, the mNeonGreen repair template was not found within the BFD1 locus, indicating that this construct had randomly integrated into the parasite genome.

Generation of bag1-OVA parasites was performed by first generating the pbag1OVA/sagCAT plasmid (Supplementary Data 1) which contains (1) the BAG1 promoter upstream of (2) the last 31 amino acids of the T. gondii major glycosyl-phosphatidylinositol-anchored surface antigen, P30, containing the signal sequence for targeting this protein to the parasitophorous vacuole, followed by (3) amino acids 140–386 of ovalbumin (OVA) and (4) a 3′ untranslated region of the dihydrofolate reductase-thymidylate synthase gene (3′dhfr). The OVA-3′dhfr fragment was subcloned in place of the red fluorescent protein (RFP)-3′dhfr fragment of the pbag1RFP/sagCAT plasmid⁹⁴ via BglII/NotI restriction digests. Transfections of type II Pruginaud (Pru) strain parasites were performed using electroporation, and stably expressing parasites were selected with chloramphenicol. Clonal parasite lines were generated by limiting dilution.

Immunohistochemistry

Brains were dissected by a sagittal cut along the midline, collected in 10% formalin, embedded in paraffin and sectioned. For identification of T. gondii parasites, slides were hydrated, and antigen was retrieved with 0.01 M sodium citrate buffer at pH 6.0, endogenous peroxidase was blocked with 0.3% H₂O₂, and sections were blocked with 2% goat serum. Parasites were detected with rabbit anti-T. gondii polyclonal antibody (gift from F. Araujo, Palo Alto Medical Foundation, 1:1,000) followed by biotinylated goat anti-rabbit IgG antibody (Vector Laboratories). Avidin-biotin complex (ABC) reagent and 3,3′-diaminobenzidine (DAB) substrate (Vector Laboratories) were used according to manufacturer’s protocol to visualize parasite staining, and haematoxylin staining was applied to visualize nuclei. Images were acquired with a Leica DM6000 Widefield Fluorescence Microscope using LAS X version 3.7.4.23463 software.

Pathological assessment

Brains were collected and processed for sectioning as described above. Haematoxylin and eosin (H&E)-stained sagittal sections of the brain, including the cerebral cortex and basal nuclei (Fig. 5 and Extended Data Fig. 5) or cerebral cortex and basal nuclei, hippocampus, thalamus, midbrain, cerebellum, pons and medulla (all other assessments) were assessed by a board-certified veterinary pathologist. The type of inflammatory cells and semiquantitative scores for the severity of parameters of interest (inflammation, haemorrhage, gliosis, necrosis and presence of parasites) were recorded for individual animals.

Flow cytometry

Single-cell suspensions were plated at up to 2 × 10⁶ cells. Cells were Fc receptor blocked for 20 min with 0.5 μg ml⁻¹ αCD16/32 (Clone 2.4G2) and 0.25% normal rat serum in FACs buffer (2% BSA and 0.02 mM EDTA in PBS) at 4 °C. If staining for tetramer, cells were then washed and incubated with 1:200 to 1:400 dilution of tetramer in FACs buffer at room temperature for 30 min. Following Fc blocking or tetramer stain, surface stain was applied, and cells were incubated for 30 min at 4 °C. Cells were then washed and resuspended in 0.1% paraformaldehyde in FACs buffer. If staining for intracellular antigens, cells were fixed and permeabilized with eBioscience Foxp3/Transcription Factor Staining Buffer Set according to manufacturer’s protocol. Cells were then stained for intracellular antigens in permeabilization buffer for 30 min at 4 °C. Cells were washed and resuspended in FACs buffer. Stained cells were acquired on a BD LSR Fortessa, BD FACSymphony A5 or BD FACSymphony A3 using BD FACS DIVA v9.0 software. Analysis was performed with FlowJo v10.7.2. Gate placement was determined based on samples stained with all fluorescent antibodies used in the flow panel except the marker of interest. Gating strategies used to identify the populations analysed in these studies can be found in Extended Data Fig. 1d (OT-I T cells) and Supplementary Fig. 6 (CNS immune populations).

The following antibodies and reagents were used for staining: B220: BUV496, BD Biosciences: 612950, clone: RA3-6B2, RRID:AB_2870227, dilution 1:300; CD3: APC-ef780, Invitrogen: 47-0032-82, clone: 17A2, RRID:AB_1272181, dilution 1:300; CD3: BUV737, BD Biosciences: 612803, clone: 17A2, RRID:AB_2738781, dilution 1:300; CD3e: PE-cf594, BD Biosciences: 562286, clone: 145-2C11, RRID:AB_11153307, dilution 1:300; CD4: BUV496, BD Biosciences: 612952, clone: GK1.5, RRID:AB_2813886, dilution 1:200; CD4: BV650, Biolegend: 100555, clone: RM4-5, RRID:AB_2562529, dilution 1:400; CD4: FITC, eBioscience: 11-0041-85, clone: GK1.5, RRID:AB_464892, dilution 1:200; CD4: APC-ef780, Invitrogen: 47-0041-82, clone: GK1.5, RRID:AB_11218896, dilution 1:300; CD8a: BUV563, BD Biosciences: 748535, clone: 53-6.7, RRID:AB_2872946, dilution 1:200; CD8a: BUV615, BD Biosciences: 613004, clone: 53-6.7, RRID:AB_2870272, dilution 1:200; CD8a: BV650, Biolegend: 100742, clone: 53-6.7, RRID:AB_2563056, dilution 1:200; CD8b: APC-ef780, Invitrogen: 47-0083-82, clone: eBioH35-17.2, RRID:AB_2573943, dilution 1:200; CD11a: BUV805, BD Biosciences: 741919, clone: 2D7, RRID:AB_2871232, dilution 1:300; CD11b: BV650, Biolegend: 101259, clone: M1/70, RRID:AB_2566568, dilution 1:500; CD19: BUV395, BD Biosciences: 563557, clone: 1D3, RRID:AB_2722495, dilution 1:300; CD45: AF647, Biolegend: 103124, clone: 30-F11, RRID:AB_493533, dilution 1:200; CD45.1: ef450, Invitrogen: 48-0453-82, clone: A20, RRID:AB_1272189, dilution 1:200; CD45.1: BV711, Biolegend: 110739, clone: A20, RRID:AB_2562605, dilution 1:200; CD45.1: PE-Cy7, Biolegend: 110730, clone: A20, RRID:AB_1134168, dilution 1:200; CD45.2: APC, Biolegend: 109814, clone: 104, RRID:AB_389211, dilution 1:200; CD45.2: BV711, Biolegend: 109847, clone: 104, RRID:AB_2616859, dilution 1:200; CD69: BUV737, BD Biosciences: 612793, clone: H1.2F3, dilution 1:200; CD69: PerCP-Cy5.5, eBioscience: 45-0691-82, clone: H1.2F3, RRID:AB_1210703, dilution 1:400; CD103: PE, eBioscience: 12-1031-81, clone: 2E7, RRID:AB_11150242, dilution 1:200; CD103: BV605, Biolegend: 121433, clone: 2E7, RRID:AB_2629724, dilution 1:200; CD107a: PE-Cy7, Biolegend: 121620, clone: 1D4B, RRID:AB_2562146, dilution 1:300; CD127: BV421, Biolegend: 135027, clone: A7R34, RRID:AB_2563103, dilution 1:200; CTLA-4: APC-R700, BD Biosciences: 565778, clone: UC10-4F10-11, RRID:AB_2739350, dilution 1:200; CX3CR1: BV785, Biolegend: 149029, clone: SA011F11, RRID:AB_2565938, dilution 1:400; CX3CR1: PerCP-Cy5.5, Biolegend: 149009, clone: SA011F11, RRID:AB_2564493, dilution 1:400; F4/80: APC-ef780, eBiosciences: 47-4801-82, clone: BM8, RRID:AB_2735036, dilution 1:200; GFP: AF488, Biolegend: 338008, clone: FM264G, RRID:AB_2563288, dilution 1:300; H-2Kb: AF647, Biolegend: 116512, clone: AF6-88.5, RRID:AB_492917, dilution 1:200; I-A/I-E: AF700, Biolegend: 107622, clone: M5/144.15.2, RRID:AB_493727, dilution 1:300; I-A/I-E: BV711, Biolegend: 107643, clone: M5/144.15.2, RRID:AB_2565976, dilution 1:1200; IFNγ: BUV737, BD Biosciences: 612769, clone: XMG1.2, dilution 1:200; Ki-67: BV470, BD Biosciences: 566109, clone: B56, RRID:AB_2739511, dilution 1:200; KLRG1: BUV395, BD Biosciences: 740279, clone: 2F1, RRID:AB_2740018, dilution 1:200; Ly-6C: BV785, Biolegend: 128041, clone: HK1.4, RRID:AB_2565852, dilution 1:600; Ly-6G: BUV563, BD Biosciences: 612921, clone: 1A8, RRID:AB_2870206, dilution 1:400; NK1.1: BUV395, BD Biosciences: 564144, clone: PK136, RRID:AB_2738618, dilution 1:300; PD-1: BV421, Biolegend: 135221, clone: 29 F.1A12, RRID:AB_2562568, dilution 1:200; PD-1: BV605, Biolegend: 135220, clone: 29 F.1A12, RRID:AB_2562616, dilution 1:200; PD-1: BV785, Biolegend: 135225, clone: 29 F.1A12, RRID:AB_2563680, dilution 1:200; T-bet: AF647, Biolegend: 644804, clone: 4B10, RRID:AB_1595466, dilution 1:200; TCRβ: PerCP-Cy5.5, Biolegend: 109228, clone: H57-597, RRID:AB_1575173, dilution 1:500; TCRβ: ef450, Invitrogen: 48-5961-82, clone: H57-597, RRID:AB_11039532, dilution 1:200; Tetramer MHCI (OVA): PE, NIH Tetramer Core, peptide: SIINFEKL, dilution 1:300; Tetramer MHCI (Tgd057): APC, NIH Tetramer Core, peptide: SVLAFRRL, dilution 1:300; Tetramer MHCII (AS15): APC, NIH Tetramer Core, peptide: AVEIHRPVPGTAPPS, dilution 1:400; Tim3: BV605, Biolegend: 119721, clone: RMT3-23, RRID:AB_2616907, dilution 1:200; TNF: APC, Invitrogen: 17-7321-82, clone: MP6-XT22, RRID:AB_469508, dilution 1:200; Vα2 TCR: BUV615, BD Biosciences: 751416, clone: B20.1, RRID:AB_2875415, dilution 1:400; Vα2 TCR: PE, Biolegend: 127808, clone: B20.1, RRID:AB_1134183, dilution 1:300; Viability: GhostDye Violet 510, TONBO Biosciences: 13-0870-T100, dilution 1:300; Viability: GhostDye Red 780, TONBO Biosciences: 13-0865-T100, dilution 1:300.

T-cell peptide restimulation

Whole splenocytes or brain leukocytes were plated at a constant cell concentration. Cells were incubated with 1 μM SIINFEKL (OVA peptide), SVLAFRRL (Tgd057 peptide) or AVEIHRPVPGTAPPS (AS15 peptide) and fluorescently labelled αLAMP1 antibody for 2 h, followed by a further 2 h with Protein Transport Inhibitor Cocktail (Invitrogen: 00-4980-03). Cells were analysed for degranulation and cytokine production by flow cytometry.

Fluorescent imaging

Brains were collected from mice after cardiac perfusion with heparin (10 U ml⁻¹) in 0.9% saline followed by 4% paraformaldehyde, fixation in 4% paraformaldehyde for 24 h and cryoprotection at 4 °C in 30% sucrose for at least 24 h. Sagittal sections (40 μm) were cut on a freezing microtome and stored at 4 °C in cryoprotectant (0.05 M sodium phosphate buffer with 30% glycerol and 30% ethylene glycol). Staining and imaging for neurons, astrocytes, dolichos biflorus lectin and OVA in infected brains was performed using the following reagents and antibodies: anti-OVA, Abcam: ab181688, dilution 1:200; DBA, Vector laboratories: B1035, dilution 1:500; anti-GFAP, DAKO: Z0334, dilution 1:200; anti-MAP2, Abcam: ab5392, dilution 1:2,000; anti-NeuN, Millipore: MAB3778, dilution 1:200; anti-Neurofilament, Abcam: ab4680, dilution 1:20,000. Anti-SAG1 (DG52), dilution 1:500 and SRS9, dilution 1:2,000 antibodies were gifted by J. Boothroyd^95,96. Stained sections were mounted on slides using ProLong Diamond Anti-Fade Mountant with DAPI (Invitrogen P36962) according to manufacturer’s protocol. Images were acquired on a Zeiss LSM 880 inverted confocal microscope (University of Arizona, Imaging Core) and Nikon E600 upright widefield microscope (University of Pennsylvania, Penn Vet Imaging Core); images were analysed using Zen 2.6 blue edition software and counted using ImageJ version 1.53 v software.

For quantification of cyst size in WT and Stat1^ΔNEU mice, perfused brains were frozen in Optimal Cutting Temperature Compound (Fisher Scientific, catalogue number 23-730-571), and 10 μm sections were cut on a vibratome. Sections were mounted with ProLong Diamond Anti-Fade Mountant with DAPI. Sections were imaged on a Leica SP5-II at ×60 magnification. Cysts were defined as vacuoles with >32 parasites present. Cyst area was quantified using Imaris (v9.7.2) microscopy imaging software, and images were generated with LAS AF (v2.7.3.9723) software. Five to 20 vacuoles per brain were quantified.

Imaging of bag1-OVA parasites in vitro was performed using HFFs cultured on eight-well chamber slides. Cells were infected at multiplicity of infection (MOI) = 3 for 3 h. Stress-induced cyst formation was performed by culturing infected cells under cyst-inducing conditions for 4 days: cells were incubated without supplemental CO₂ in RPMI media (pH 8.0) without sodium bicarbonate, supplemented with 1% FBS, 10 mg ml⁻¹ HEPES, 100 U ml⁻¹ penicillin and 100 µg ml⁻¹ streptomycin. Media was replaced every 48 h (ref. ⁶⁴). Cells were then stained with anti-OVA (Abcam ab181688) and DAPI nuclear stain. Slides were imaged on a Nikon E600 upright widefield microscope (University of Pennsylvania Imaging Core).

Quantification of serum IFNγ

Blood was collected by submandibular bleed and clotted at room temperature for 1 h. Serum was separated through centrifugation for 10 min at 14,000 g. Serum was diluted between 1:5 and 1:20, and IFNγ levels were assayed by BD Mouse IFNγ Flex Set Cytometric Bead Array according to manufacturer’s protocol. Beads were analysed by flow cytometry on a BD Canto.

Quantification of parasite burden by quantitative PCR

Sagittal sections of brain tissue were snap frozen and stored at −20 °C. DNA was isolated using QIAGEN DNeasy Blood and Tissue Kit according to manufacturer’s protocol. DNA quality and concentration was assessed on a Nanodrop ND-1000 UV–Vis Spectrophotometer. About 200 ng of DNA was used to quantify parasite burden by quantitative PCR (qPCR) with Power SYBR Green Master Mix and primers specific for the T. gondii B1 gene (Supplementary Data 1). qPCR was performed on Applied Biosystems ViiA7 with the following conditions: hold phase for 2 min at 50 °C and 10 min at 95 °C; PCR phase (occurs 50 times) for 15 s at 95 °C and 1 min at 60 °C.

Statistical information

Statistical tests were run in Prism software version 10.2.3 (Graphpad). Data were analysed by two-sided Student’s t-tests, two-sided Student’s t-tests with Bonferroni–Dunn correction for multiple tests, two-way analysis of variance (ANOVA) or two-sided Mann–Whitney tests where indicated. Not significant, P ≥ 0.05; *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. Precise P values for significant trends are included in the corresponding figure legends.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

Source data are provided with this paper.

Code availability

All code relating to the generation of ODEs are available on GitHub using the link provided: https://github.com/acwinn/TGondii.

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Acknowledgements

We thank A. T. Phan for contributions and assistance with experiments. We also thank G. Ruthel and the Penn Vet Imaging Core for kindly providing microscopy equipment, assistance with image acquisition and access to imaging analysis software. These studies were supported by funding from the National Institutes of Health, R01 AI157247 (C.A.H. and A.A.K.); National Institute of Allergy and Infectious Diseases, U01 AI160664 (D.A.C.), F31 AI161962 (D.L.A.), T32 CA009140 (M.E.B.) and R01 AI158501 (S.L.); and Institutional funding from the College of Medicine and BIO5 Institute of the University of Arizona (A.A.K.).

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These authors contributed equally: Julia N. Eberhard, Lindsey A. Shallberg, Aaron Winn.

Authors and Affiliations

Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, USA
Julia N. Eberhard, Lindsey A. Shallberg, David A. Christian, Daniel L. Aldridge, Molly E. Bunkofske, Maxime Jacquet & Christopher A. Hunter
Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, USA
Aaron Winn & Eleni Katifori
BIO5 Institute, University of Arizona, Tucson, AZ, USA
Sambamurthy Chandrasekaran & Anita A. Koshy
Whitehead Institute for Biomedical Research, Cambridge, MA, USA
Christopher J. Giuliano & Sebastian Lourido
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
Christopher J. Giuliano & Sebastian Lourido
Department of Immunology, University of Arizona, Tucson, AZ, USA
Emily F. Merritt & Anita A. Koshy
Comparative Pathology Core, Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA, USA
Elinor Willis
Department of Comparative Pathobiology, Purdue University College of Veterinary Medicine, West Lafayette, IN, USA
Christoph Konradt
The Royal Ottawa Mental Health Center, Institute of Mental Health Research, Ottawa, Ontario, Canada
Florence Dzierszinski
Center for Computational Biology, Flatiron Institute, New York, NY, USA
Eleni Katifori
Department of Neurology, University of Arizona, Tucson, AZ, USA
Anita A. Koshy

Authors

Julia N. Eberhard
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Lindsey A. Shallberg
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Aaron Winn
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Sambamurthy Chandrasekaran
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Christopher J. Giuliano
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Emily F. Merritt
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Elinor Willis
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Christoph Konradt
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David A. Christian
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Daniel L. Aldridge
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Molly E. Bunkofske
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Maxime Jacquet
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Florence Dzierszinski
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Eleni Katifori
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Sebastian Lourido
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Anita A. Koshy
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Christopher A. Hunter
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Contributions

Conceptualization: L.A.S., C.A.H., A.A.K. and S.L. Methodology: L.A.S., A.W., J.N.E., S.C., C.J.G., E.F.M. and F.D. Investigation: L.A.S., J.N.E., A.W., S.C., C.J.G., E.F.M., E.W., C.K., D.A.C., D.L.A., M.E.B. and M.J. Funding acquisition: L.A.S., C.A.H., A.A.K., S.L. and E.K. Supervision: L.A.S., C.A.H., A.A.K., S.L., F.D. and E.K. Writing—original draft: L.A.S. and C.A.H. Writing—review and editing: J.N.E., C.A.H., A.W., A.A.K., S.L., S.C., E.W., D.A.C., M.E.B. and L.A.S.

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Correspondence to Christopher A. Hunter.

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Nature Microbiology thanks Jason Gigley and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Virulence and T cell responses during early stages of tub1-OVA and bag1-OVA infection.

a, Representative images of in vitro bag1-OVA tachyzoite- or cyst-infected HFFs, and in vivo bag1-OVA tissue cysts in the brains of mice at 30 dpi. Samples were stained with DAPI nuclear stain and anti-OVA antibody. DAPI (blue); OVA (green). Scale bar = 10 μm. b-c, C57BL/6 J mice were infected with tub1-OVA (n = 7 mice) or bag1-OVA (n = 5 mice) parasites, and spleens were harvested and analyzed at 10 dpi. b, Frequency and number of T. gondii peptide and SIINFEKL tetramer⁺ CD4⁺ and CD8⁺ T cells (***p = 0002.) c, Quantification of parasite burden by qPCR. d, Gating strategy for identifying OT-I T cells by flow cytometry. Cells were pre-gated on single cells. e, Experimental design for f-g. Naive CD45.1⁺CD45.2⁺ Nur77^GFP OT-I T cells were transferred 1 day prior to infection with tub1-OVA or bag1-OVA parasites. Spleens and brains were harvested from infected mice and analyzed by flow cytometry during acute (n = 3 mice/group) and chronic (tub1-OVA, n = 5 mice; bag1-OVA, n = 3 mice) infection. f, Frequency and number of OT-I T cells (spleen: ****p = 0.000036, ***p = 0.000535; brain: **p = 0.001260, ***p = 0.000411.) g, Frequency and gMFI of Nur77^GFP expression in brain OT-I T cells during chronic infection (tub1-OVA, n = 5 mice; bag1-OVA, n = 3 mice.) Data are representative of 2 independent experiments. Data analyzed by two-sided unpaired Student’s t-test; ns p > 0.05. Bar graphs depict the mean ± SD.

Source data

Extended Data Fig. 2 Similar T. gondii specific T cell responses are induced in the brains of WT and Stat1^ΔNEU mice at 3 months post-infection.

Brains from C57BL/6 J (WT) and Stat1^ΔNEU mice infected with T. gondii were harvested at 3 mpi (n = 3 mice/group.) T. gondii-specific T cells were quantified and phenotyping was performed by flow cytometry. a, Frequency and number of T. gondii tetramer⁺ CD8⁺ T cells. b, UMAP and X-shift unsupervised clustering analysis of tetramer⁺ T cells. Colors represent 12 individual clusters. c, Distribution of tetramer⁺ T cells across the clusters identified in b. d-f, Phenotyping of tetramer⁺ CD8⁺ T cells by flow cytometry. Data are representative of 2 independent experiments. Data analyzed by two-sided unpaired Student’s t-test; Bonferroni-Dunn correction for multiple comparisons was included in statistical analyses performed in c and d; ns p > 0.05. Bar graphs depict the mean ± SD.

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Extended Data Fig. 3 WT and Δbfd1 parasites induce comparable immune responses during acute infection.

a-b, C57BL/6 J mice were infected with tdTomato⁺ WT (n = 4 mice) or Δbfd1 (n = 5 mice) parasites, and spleens were harvested and analyzed at 14 dpi. Naive CD45.1⁺CD45.2⁺ OT-I T cells were transferred one day prior to infection. a, Quantification of T. gondii-infected cells in the spleen by flow cytometry b, Splenic OT-I T cell frequency and numbers. c, Quantification of serum IFN-γ levels during WT (n = 4 mice) or Δbfd1 (n = 5 mice) infection. d, Representative images of T. gondii in the brains of mice 25 dpi with WT or Δbfd1 parasites. Brain sections were stained with DBA and either anti-SAG1 antibody (top row) or anti-SRS9 antibody (bottom row). SAG1 or SRS9 (red); tdTomato (green); DBA (purple). Scale bar = 10 μm. Data are representative of 2 independent experiments. Data analyzed by two-sided unpaired Student’s t-test; ns p > 0.05. Bar graphs depict the mean ± SD.

Source data

Extended Data Fig. 4 Immune responses and pathology in the brain during chronic WT and Δbfd1 infection.

Brains were harvested from C57BL/6 J naïve mice and mice 30 dpi with WT or Δbfd1 parasites and analyzed as described. a, Detailed semiquantitative pathological scoring of brain histology sections. b, Cumulative pathology score based on the parameters shown in a (WT, n = 3 mice; Δbfd1, n = 4 mice.) c,d, Flow cytometry analysis of brains from naïve mice (n = 4 mice) and mice at 30 dpi with WT (n = 5 mice) or Δbfd1 (n = 3 mice) parasites (**p = 0.0093, *p = 0.0349, ****p = <0.0001; Data representative of 3 independent experiments). c, Quantification of CNS immune populations. d, Heatmaps displaying MFI of phenotypic markers used to identify UMAP clusters in Fig. 5e,f. e-g, Naive CD45.1⁺CD45.2⁺ OT-I T cells were transferred i.v. into mice 1 day prior to infection with WT (n = 3 mice) or Δbfd1 (n = 4 mice) parasites. Brains were harvested and analyzed by flow cytometry (Data representative of 2 independent experiments.) e, UMAP analysis of OT-I T cells at 14 and 30 dpi. f, Frequency of CD69⁺CD103⁺ OT-I T cells at 30 dpi (**p = 0.0053.) g, KLRG1 and CX3CR1 expression on OT-I T cells at 30 dpi (*p = 0.016035.). Data analyzed by two-sided Mann-Whitney test (b) or two-sided unpaired Student’s t-test (c,f,g); Bonferroni-Dunn correction for multiple comparisons was included in g; ns p > 0.05. Bar graphs depict the mean ± SD.

Source data

Extended Data Fig. 5 CNS inflammation and pathology associated with Δbfd1 infection across mouse and parasite strains.

a-f, BALB/c mice were infected with WT or Δbfd1 parasites. Brains were harvested and analyzed at 30 dpi. a, Survival of mice until time of harvest. b, Quantification of CNS immune cell populations measured by flow cytometry (in order of appearance: **p = 0.0020, **p = 0.0013, **p = 0.0039, **p = 0.0010, *p = 0.0299.) Gating scheme to identify CNS immune populations is depicted in Supplementary Fig. 6. c,d, Cumulative pathology score (c) and detailed pathological assessment (d) of brain histology sections. Assessment was performed by a board-certified veterinary pathologist. e, Representative photomicrographs of the brain showing the parenchyma (top) and meninges (bottom) in the cerebrum at 30 dpi. Inset and black arrow show tachyzoites in the brain during Δbfd1 infection. f, Quantification of CNS parasite burden by qPCR. Data are representative of 1 experiment with n = 5 mice/group. Data analyzed by two-sided unpaired Student’s t-test (b,f) or two-sided Mann-Whitney test (c); ns p > 0.05. Bar graphs depict the mean ± SD.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–6, Tables 1 and 2 and text.

Reporting Summary

Supplementary Data 1

Unique oligonucleotides used in this study.

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Source Data Fig. 2

Numerical and statistical source data for Fig. 2.

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Numerical and statistical source data for Fig. 3.

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Numerical and statistical source data for Fig. 4.

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Numerical and statistical source data for Fig. 5.

Source Data Extended Data Fig. 1

Numerical and statistical source data for Extended Data Fig. 1.

Source Data Extended Data Fig. 2

Numerical and statistical source data for Extended Data Fig. 2.

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Numerical and statistical source data for Extended Data Fig. 3.

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Numerical and statistical source data for Extended Data Fig. 4.

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Numerical and statistical source data for Extended Data Fig. 5.

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Eberhard, J.N., Shallberg, L.A., Winn, A. et al. Immune targeting and host-protective effects of the latent stage of Toxoplasma gondii. Nat Microbiol 10, 992–1005 (2025). https://doi.org/10.1038/s41564-025-01967-z

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Received: 18 August 2022
Accepted: 19 February 2025
Published: 27 March 2025
Issue date: April 2025
DOI: https://doi.org/10.1038/s41564-025-01967-z

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Abstract

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Main

Results

Modelling stage-specific immunity to T. gondii in the CNS

Cyst-derived antigen induces a CD8+ T-cell response

Neuronal STAT1 mediates cyst control

Cyst formation is not required for parasite persistence

Cyst formation is host protective

Discussion

Methods

Mice

Infections and T-cell transfers

IFNγ blockade and sulfadiazine treatment

Tissue processing and cell counting

Generation of transgenic parasites

Immunohistochemistry

Pathological assessment

Flow cytometry

T-cell peptide restimulation

Fluorescent imaging

Quantification of serum IFNγ

Quantification of parasite burden by quantitative PCR

Statistical information

Reporting summary

Data availability

Code availability

References

Acknowledgements

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Cyst-derived antigen induces a CD8⁺ T-cell response