The latent stage ofToxoplasma gondiiis targeted by the immune response and host protective

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Shallberg , View ORCID Profile Julia N. Eberhard , Aaron Winn , Sambamurthy Chandrasekaran , View ORCID Profile Christopher J. Giuliano , Emily F. Merritt , Elinor Willis , View ORCID Profile David A. Christian , View ORCID Profile Daniel L. Aldridge , View ORCID Profile Molly Bunkofske , Maxime Jacquet , Florence Dzierszinski , Eleni Katifori , View ORCID Profile Sebastian Lourido , Anita A. Koshy , View ORCID Profile Christopher A. Hunter doi: https://doi.org/10.1101/2024.03.05.583527 Lindsey A. Shallberg 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Julia N. Eberhard 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Julia N. Eberhard Aaron Winn 2 Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania; Philadelphia , PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sambamurthy Chandrasekaran 3 BIO5 Institute, University of Arizona ; Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christopher J. Giuliano 6 Whitehead Institute for Biomedical Research ; Cambridge, MA 02142, USA 7 Department of Biology, Massachusetts Institute of Technology ; Cambridge, MA 02142, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Christopher J. Giuliano Emily F. Merritt 4 Department of Immunology and University of Arizona ; Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elinor Willis 8 Comparative Pathology Core, Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site David A. Christian 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for David A. Christian Daniel L. Aldridge 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Daniel L. Aldridge Molly Bunkofske 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Molly Bunkofske Maxime Jacquet 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Florence Dzierszinski 9 The Royal Ottawa Mental Health Center, Institute of Mental Health Research ; Ottawa, Ontario, K1Z 7K4, Canada Find this author on Google Scholar Find this author on PubMed Search for this author on this site Eleni Katifori 2 Department of Physics and Astronomy, School of Arts and Sciences, University of Pennsylvania; Philadelphia , PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sebastian Lourido 6 Whitehead Institute for Biomedical Research ; Cambridge, MA 02142, USA 7 Department of Biology, Massachusetts Institute of Technology ; Cambridge, MA 02142, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Sebastian Lourido Anita A. Koshy 3 BIO5 Institute, University of Arizona ; Tucson, AZ 85721, USA 4 Department of Immunology and University of Arizona ; Tucson, AZ 85721, USA 5 Department of Neurology, University of Arizona ; Tucson, AZ 85721, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site Christopher A. Hunter 1 Department of Pathobiology, School of Veterinary Medicine and University of Pennsylvania ; Philadelphia, PA 19104, USA Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Christopher A. Hunter For correspondence: chunter{at}vet.upenn.edu Abstract Full Text Info/History Metrics Supplementary material Preview PDF Abstract Latency is a microbial strategy for persistence. For Toxoplasma gondii the ability of the bradyzoite stage to form long-lived cysts is critical for transmission, while their presence in neurons is considered important for immune evasion. Development of a mathematical model highlighted that immune pressure on bradyzoites should contribute to dynamics of cyst formation and reactivation. Experimental data demonstrated that a cyst-derived antigen was recognized by CD8 + T cells and that IFN-γ signaling in neurons contributes to cyst control. In addition, modeling and the use of a parasite strain unable to form bradyzoites revealed that this stage was not required for long-term persistence, but the absence of cyst formation resulted in increased tachyzoite replication in the CNS with associated tissue damage and mortality. Thus, the latent form of T. gondii is under immune pressure, mitigates infection-induced damage, and promotes survival of host and parasite. Introduction Many infections can lead to an asymptomatic chronic state associated with low levels of micro-organisms despite the presence of protective immunity. For a subset of diverse viral and parasitic pathogens, persistence is linked to transition from a lytic to a non-lytic, latent developmental state. These quiescent stages are difficult to treat, and the absence of tractable models of natural host-pathogen interactions has left a gap in our understanding of the role of latency in immune evasion and persistence and its impacts on human health 1 , 2 . Latency is considered an evolutionarily conserved strategy for immune evasion that aids in persistence, while periodic reactivation is associated with disease and increased levels of transmission 3 – 8 . For example, the Sarcocystidae family of apicomplexan parasites (which includes Toxoplasma gondii ) converts from the tachyzoite stage to the slow growing bradyzoite stage which forms long-lived tissue cysts found predominantly in neurons 6 , 9 – 11 . The molecular basis for this switch is mediated by the transcription factor BFD1 and the RNA binding protein BFD2 that enforce and maintain the bradyzoite transcriptional program 12 – 14 . This latent stage facilitates oral transmission and has been considered important for immune evasion, making it a major contributor to the evolutionary success of this parasite 15 . T. gondii provides a system to study natural host-pathogen interactions in mice, and its genetic tractability has led to the development of a diverse toolkit to dissect how the immune system promotes long-term resistance to this organism 16 , 17 . The acute phase of infection is dominated by systemic dissemination of the lytic tachyzoite stage, which invades and replicates in many cell types and is associated with significant tissue damage. While this early phase of infection is controlled by the immune system, the chronic phase is characterized by conversion to the bradyzoite stage and the persistence of cysts predominantly within neurons of the central nervous system (CNS) 10 , 11 . While the cyst is largely considered dormant and the cyst wall impermeant, its relationship with the host cell is more dynamic than previously thought 18 – 20 . Cyst burden and size have been shown to change over time, and the ability of cysts to undergo periodic reactivation contributes to recrudescence and active disease in patients with acquired immune deficiencies that affect T cell function 11 , 21 – 23 . Resistance to T. gondii is marked by a balance between the ability to limit the tissue damage that results from tachyzoite replication versus the immune pathology associated with this infection. Thus, there are numerous host tolerance mechanisms that act to limit aberrant inflammation in the systemic phase of this infection as well as the immune pathology associated with the presence of T. gondii in the CNS 24 – 29 . Many features of the brain contribute to its status as an immune privileged site 30 , 31 . Neurons have low basal levels of MHC class I and a reduced ability to respond to IFN-γ, features that have led to the concept that these long-lived cells provide a refuge for certain viral and parasitic pathogens 31 – 34 . This perspective is challenged by reports of CD8 + T cell recognition and killing of virally-infected neurons and evidence of non-cytopathic IFN-γ-mediated mechanisms of viral clearance from neurons 35 – 39 . Previous reports suggested that IFN-γ did not promote control of tachyzoites in neurons, however, more recent work has highlighted that extended incubation of neurons with IFN-γ limits parasite growth 34 , 40 . IFN-γ is considered the major mediator of resistance to T. gondii , but there is also evidence that a CD8 + T cell-mediated, perforin-dependent mechanism contributes to parasite control in the CNS and that CD8 + T cells can recognize neurons infected with tachyzoites 41 – 44 . Evidence that neurons containing cysts are directly targeted by CD8 + T cells is lacking, but there are reports that microglia and CD8 + T cells can interact with the cyst stage 42 , 45 – 49 . In mouse models, infection dynamics are characterized by a peak of cysts in the CNS in the first 3-5 weeks of infection and an increase in cyst size followed by a slow decline in cyst numbers 18 , 21 , 50 , 51 . Whether periodic cyst reactivation provides the immune response the opportunity to eliminate new tachyzoites and thereby limit formation of new cysts or there is a more direct immune-mediated mechanism to eliminate bradyzoites is unclear. The ability to quantify T cell responses and changes in parasite burden during murine toxoplasmosis has been used as the basis for mathematical models to describe different facets of immunity to this infection 52 – 55 . Here, a series of ordinary differential equations (ODE) were developed to integrate how the immune response to different developmental stages of T. gondii might influence parasite dynamics. This model suggested the presence of immune-mediated cyst control and that cycles of cyst formation and reactivation are important for oscillations in parasite burden and CNS inflammation. To test these predictions, a combination of 1. transgenic parasites with stage-specific expression of the model antigen OVA, 2. parasites unable to form cysts, and 3. mice with blunted neuronal IFN-γ signaling were used. Together, these data reveal that an immune response is elicited against the latent form of T. gondii, and while this stage is not essential for persistence, the cyst provides a replicative sink required to mitigate infection-induced damage and thereby promote mutual survival of host and parasite. Results Modeling of parasite dynamics in the CNS predicts the presence of immune pressure on tachyzoites and bradyzoites To investigate the relationship in the CNS between tachyzoite replication, cyst formation, reactivation, and the immune response, a system of ordinary differential equations (ODEs) was generated. A detailed derivation of the ODE system, explanation of the rate constants, and comparisons to the previous model are given in Supplementary Text section 1. The approach utilized is similar to that of Sullivan et al. 52 but considers the possibility of immune pressure on bradyzoites. Two key assumptions of this model are that after tachyzoite entry to the CNS most of the host cells remain uninfected, and parasites spend the majority of their lifetime within infected cells. Important parameters are the numbers of tachyzoite-infected cells ( I T ) , bradyzoite-infected cells ( I B ) , and immune cells (Z). The number of tachyzoite-infected cells increases at a rate β T while the differentiation of tachyzoites to bradyzoites occurs at a rate c TB . The absence of cyst formation would yield a c TB = 0. While individual cyst growth in vivo is known to be asynchronous 18 , the parameter here considers the growth rate of the whole population as being synchronized. Bradyzoite reactivation is represented by the ability of bradyzoites to re-infect cells and give rise to tachyzoites at a rate β B . Cells infected with either tachyzoites or bradyzoites may rupture (at a rate d T or d B ) or be cleared in the presence of immune cells (at a rate ψ T or ψ B ). Tachyzoite- or bradyzoite-infected cells trigger the immune response at a rate a T or a B . Here, the feedback between the immune response and infection takes the form of a predator-prey interaction: in the absence of an immune response parasite growth is unrestricted, but when immune cells are produced they limit parasite replication or lead to the elimination of infected cells. With decreased parasite burden, immune cells contract at a rate µ . Note that the nonlinear terms are normalized by the initial total uninfected cell number S 0 (which essentially remains constant in our experiment) such that all rates are intensive. The system can be represented as a Petri net 56 with compartments shown as circles and reactions as squares ( Fig. 1a ). In this visualization, the two arrows from β T to I T represent a +1 increase in parasite numbers and similarly these two arrows are also used to represent the ability of infected cells ( α T /α B ) to amplify the immune response (Z). The corresponding system of ODEs is given in equations (1), (2), and (3). Download figure Open in new tab Fig. 1: Compartmental modeling of T. gondii infection in the CNS predicts the presence of immune responses to tachyzoites and bradyzoites. a , Petri net representing the dynamics in equations (1), (2), and (3). Each square represents a particular reaction, with arrows entering a square representing reactants and arrows leaving a square representing products. b , Nine numerical results to (1), (2), and (3). Certain parameters are set to zero to demonstrate the role of each term. When nonzero, the parameters used were S 0 = 10 8 , I T (0) = 1, I B (0) = 0, Z (0) = 10 5 , β T = 1.7, β B = .2, c TB = .25, a T = 10 5 , a B = .2 ∗ 10 5 , µ = .1, ψ T = 50, ψ B = 10. Primary data from murine infection were used to estimate model parameters (Supplementary Text section 4), and a summary is presented in Table 1 . These biologically derived values were used to produce numerical solutions to equations (1), (2), and (3). By setting certain parameters equal to zero, the role of particular mechanisms can be elucidated, and several key scenarios are illustrated ( Fig. 1b ). In the top row, the immune response is disabled, and the number of tachyzoite-infected cells grows exponentially, and this remains largely unaltered even if bradyzoite differentiation and reactivation are incorporated. The solutions can be found analytically in this limit (see Supplementary Text section 2). In the second row, the inclusion of an anti-tachyzoite response alone ( ψ T ) results in the initial exponential growth of infected cells that triggers an influx of immune cells that leads to a rapid reduction in infected cells and contraction of the immune response. This is followed by cycles of tachyzoite recrudescence and control, apparent as oscillations in immune cell number. The inclusion of bradyzoite differentiation in the absence of reactivation (middle panel) predicts a larger period for the oscillations in tachyzoite-infected cell number but a stepped increase in bradyzoite numbers with each reactivation event. The inclusion of bradyzoite differentiation and reactivation in the absence of an anti-cyst response results in monotonic growth of the cyst burden (right hand panel). This simulation predicts the maintenance of immune populations which prevent significant oscillations in tachyzoite numbers. None of these scenarios in rows 1 or 2 capture all the key features of a natural infection in the CNS. View this table: View inline View popup Download powerpoint Table 1: Estimated parameter values based on empirical data in day -1 (Supplemental text). In the final set of simulations (bottom row), tachyzoite and bradyzoite specific immune responses are now incorporated – and in scenarios where differentiation to the bradyzoite is absent (left panel) this is followed by cycles of tachyzoite recrudescence and control that are similar in magnitude over the course of infection. However, when bradyzoite differentiation and reactivation are integrated ( β B = 0 or β B ≠ 0) these oscillations are reduced in frequency and dampened over time (bottom right-hand panel). A stability analysis in Supplementary Text section 3 demonstrates that both differentiation and reactivation are necessary in order to dampen oscillations in infected cell number. It is shown that when c TB = 0 the oscillations in infected cell number are undampened, and when c TB is small but non-zero the oscillations decay at a rate proportional to β B . This model implies that both differentiation and reactivation are necessary to dampen oscillations in infected cell number and immune cell infiltration. While both rupture and immune clearance can lead to a decline in cyst numbers, rupture (and the ability to form new cysts) leads to a steady value of cysts, whereas immune clearance leads to cyclic changes and an overall decline in cyst populations. Together, these models predict that to recapitulate the key features of this infection in the CNS there needs to be immune mechanisms that exert pressure on both tachyzoite and bradyzoite stages. Cyst-derived antigen induces a CD8 + T cell response To determine if cyst-derived antigen could be recognized by CD8 + T cells, transgenic parasites were generated with a cyst-specific promoter to drive expression of the model antigen OVA (bag1-OVA), and infection with bag1-OVA parasites was combined with intravenous (i.v.) transfer of T cell receptor (TCR) transgenic CD8 + OT-I T cells. The immune response to these parasites was compared to parasites that express OVA constitutively (by tachyzoites and bradyzoites) under the tubulin promoter (tub1-OVA; Fig. 2a ). In C57BL/6 mice, during the acute phase the two parasite strains established similar levels of infection and induced comparable parasite-specific endogenous CD4 + and CD8 + T cell responses in the spleen ( Extended Data Fig. 1a,b ). As expected, only tub1-OVA parasites induced an endogenous SIINFEKL-specific response at this timepoint ( Extended Data Fig. 1a ). Infection was also performed one day post-transfer of congenically distinct CD45.1 + CD45.2 + OT-I T cells that express Nur77 GFP upon recent TCR engagement ( Extended Data Fig. 1c ) 47 . OT-I T cells expanded and trafficked to the brain and spleen at 14 days post-infection (dpi) with tub1-OVA parasites, but this was not observed with bag1-OVA parasites. However, by 28 dpi, a timepoint when cyst formation is apparent in the CNS, both infections resulted in OT-I T cell populations in the brain ( Extended Data Fig. 1e ). These populations contained a subset of Nur77 GFP+ cells, indicating that these T cells had received recent TCR stimulation ( Extended Data Fig. 1f ). The magnitude of the OT-I response in the CNS was approximately 5-to 10-fold greater during infection with tub1-OVA parasites compared to bag1-OVA parasites ( Extended Data Fig. 1e ). This difference could reflect delayed priming as a result of delayed OVA expression in bag1-OVA parasites. To normalize for time of priming, naive OT-I T cells were transferred into infected mice at 21 dpi (when both parasite strains are expected to express OVA) and analyzed 2-3 weeks later ( Fig. 2b ). The OT-I T cell response induced by the bag1-OVA parasites remained lower in magnitude and there was a lower frequency of Nur77 GFP expressing cells ( Fig. 2c,d ). These data suggest that the kinetics of T cell priming do not readily account for differences in the magnitude of the OT-I T cell response or the levels of TCR engagement observed between tub1-OVA and bag1-OVA parasites. Download figure Open in new tab Extended Data Fig. 1: Virulence and T cell responses during early stages of infection with tub1-OVA and bag1-OVA parasites. a , Frequency and number of T. gondii peptide and SIINFEKL tetramer + CD4 + and CD8 + T cells from the spleens of mice 10 dpi with tub1-OVA (left, open circles) or bag1-OVA (right, open squares) parasites. b , Quantification of splenic parasite burden by qPCR at 10 dpi. c , Experimental design for d-f . 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. Brains and spleens were harvested from infected mice and analyzed by flow cytometry during acute and chronic infection. d , Gating strategy for identifying OT-I T cells by flow cytometry. e , Frequency and number of OT-I T cells in the spleen and brain of tub1-OVA or bag1-OVA infected mice during acute and chronic infection. f , Frequency and gMFI of Nur77 GFP expression in brain OT-I T cells following tub1-OVA or bag1-OVA infection. Data are representative of 2 independent experiments with 3-7 mice per group. Bar graphs depict the mean ± SD. Data analyzed by two-tailed unpaired Student’s t -test; ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Download figure Open in new tab Fig. 2: Cyst-derived antigen induces a CD8 + T cell response in the CNS. a , Transgenic parasite constructs for constitutive (tub1-OVA) and bradyzoite (bag1-OVA) restricted OVA expression. b , Experimental design for c-m . WT mice were infected intraperitoneally (i.p.) with either tub1-OVA (black, open circles) or bag1-OVA (purple, open squares) parasites. At 21 days post-infection (dpi) naïve congenically distinct (CD45.1 + CD45.2 + ) Nur77 GFP OT-I T cells were transferred intravenously (i.v.). Brains were harvested and analyzed by flow cytometry 35-45 dpi. c , Frequency and number of OT-I T cells isolated from the brain of tub1-OVA or bag1-OVA infected mice. d , Frequency and geometric mean fluorescence intensity (gMFI) of Nur77 GFP expression in OT-I T cells shown in c . e,f, UMAP analysis and unsupervised clustering of OT-I T cells pooled from tub1-OVA and bag1-OVA infected brains. Colors represent 7 individual clusters identified through X-shift clustering analysis. g , Heatmaps displaying MFI of individual phenotypic markers across the 7 clusters identified in f . h-k , Flow cytometric profiling of OT-I T cells based on the frequency and gMFI of phenotypic marker expression. Grey histogram sample indicates expression by naive CD8 + T cells. l, m , OT-I degranulation and cytokine production measured by flow cytometry after 4 hour restimulation with SIINFEKL peptide. Grey indicates unstimulated OT-I T cell controls. Data are representative plots from 3 independent experiments with 3-7 mice per group. Bar graphs depict the mean ± SD. Data analyzed by two-tailed unpaired Student’s t -test. Bonferroni-Dunn correction for multiple comparisons included in statistical analyses performed in f and h . ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. We next assessed the phenotype of OT-I T cells in the CNS responding to tub1-OVA or bag1-OVA parasites using high parameter flow cytometry. Uniform Manifold Approximation and Projection (UMAP) analysis of the concatenated OT-I T cell populations (from tub1-OVA and bag1-OVA infections) revealed 7 main clusters with varied levels of 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 induced in response to tub1-OVA displayed heterogenous T effector phenotypes that contained KLRG1 + CX3CR1 + , KLRG1 + CX3CR1 - , and KLRG1 - CX3CR1 - populations that expressed high levels of T-bet ( Fig. 2h,i ). Only a small proportion of cells were CD69 + CD103 + or PD-1 hi ( Fig. 2j,k ). By contrast, OT-I T cells induced in response to bag1-OVA infection were dominated by a KLRG1 - CX3CR1 - population with decreased T-bet expression. These cells also exhibited co-expression of tissue resident memory markers CD69 and CD103 and expressed high levels of the inhibitory receptor PD-1 ( Fig. 2h-k ). Restimulation of cells isolated from infected brains with the OVA-derived SIINFEKL peptide showed that while OT-I T cells from both infections had similar levels of degranulation (a measure of cytotoxic potential), T cells induced by bag1-OVA infection had a reduced ability to produce IFN-γ ( Fig. 2l,m ). A comparison of the OT-I T cell responses to tachyzoite-and bradyzoite-derived OVA indicates that tachyzoite-derived antigens drive the majority of the effector CD8 + T cell response in the CNS, but there is a sub-population of CD8 + T cells that respond to cyst-derived antigen, have a distinct phenotype, and reduced effector capacity. Neuronal expression of STAT1 is required for cyst control The cytokine IFN-γ is the major mediator of resistance to T. gondii and signals through STAT1 to mediate its protective effects on haematopoietic and non-haematopoietic cell types 44 , 57 . To test the role of IFN-γ in controlling T. gondii in neurons, Snap25 -Cre mice were crossed with Stat1 fl/fl mice to generate progeny ( Stat1 ΔNEU ) in which neurons have a blunted ability to respond to IFN-γ. WT and Stat1 ΔNEU mice were infected with tdTomato + parasites to measure infected cells in the CNS. At 20 dpi, a timepoint prior to extensive cyst formation in the CNS, there was no difference between WT and Stat1 ΔNEU mice in total parasite burden or the number of tdTomato + leukocytes in the CNS (a proxy for tachyzoite-specific infection due to the absence of cysts in non-neuronal cells; Fig. 3a,b ). At 3 months post-infection (mpi), total parasite burden remained comparable between WT and Stat1 ΔNEU mice ( Fig. 3c ). However, at this timepoint, cysts in Stat1 ΔNEU brains were larger (an indicator of increased longevity) and more numerous ( Fig. 3d-f ). This elevated cyst burden was not associated with increased mortality ( Fig. 3g ), and histopathological assessment of the brain did not reveal any signs of increased levels of CNS damage that would be associated with increased tachyzoite replication ( Fig. 3h,i ). In addition, there were no alterations in the numbers or phenotype of parasite-specific CD8 + T cells in the brains of these mice ( Extended Data Fig. 2a-f ). These results indicate that in vivo activation of neuronal STAT1 underlies a cell-intrinsic mechanism to control cysts. This observation is consistent with the modeling prediction that anti-cyst responses contribute to CNS parasite dynamics. Download figure Open in new tab 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. The brains from WT and Stat1 ΔNEU mice were harvested and analyzed at 3 mpi with T. gondii. T. gondii- specific T cells were quantified and phenotyped 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 with 3 mice per group. Bar graphs indicate the mean ± SD. Data analyzed by two-tailed unpaired Student’s t -test; Bonferroni-Dunn correction for multiple comparisons included in statistical analyses performed in c and d ; ns p > 0.5. Download figure Open in new tab Fig. 3: Neuronal STAT1 mediates cyst control during chronic T. gondii infection. WT and Stat1 ΔNEU mice were infected i.p. with a tdTomato-expressing Pru strain of T. gondii, and brains were analyzed 3 weeks post-infection (wpi; a,b ) or 3 months post-infection (mpi; c-f,h,i ). a,b , Quantification of CNS parasite burden by qPCR ( a ) and tdTomato + tachyzoite infected CD45 + leukocytes by flow cytometry ( b ) at 3 wpi. c , Quantification of CNS parasite burden at 3 mpi. d , Fluorescent imaging of brains from WT and Stat1 ΔNEU mice at 3 mpi. (tdTomato + parasites (Red), DAPI (blue), and white arrows indicate T. gondii cysts; scale bar = 50 μm). e,f , Brain cyst area ( e ) and number ( f ) at 3 mpi. Cysts were identified as vacuoles with >32 parasites present (5-20 cysts measured per section). g , Survival of infected WT and Stat1 ΔNEU mice. h , H&E-stained sections of brain at 3 mpi were submitted for assessment and semiquantitative scoring by a board-certified veterinary pathologist. Cumulative pathological scores for individual mice are shown. i , IHC for T. gondii on sections from the brains scored in h . (Arrows indicate T. gondii cysts; scale bar = 200 μm). Data are representative of 2 independent experiments with 3-8 mice per group. Bar graphs depict the mean ± SD. Data analyzed by ( a-c,e,f ) two-tailed unpaired Student’s t -test or ( h ) Mann-Whitney test; ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001. Cyst formation is not required for parasite persistence We next modeled the impact of cyst formation and reactivation on parasite dynamics in the CNS. 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 versus c TB = 0.25) predicted an increase in the number of tachyzoite-infected cells early after parasite invasion of the CNS ( Fig. 4a ). In this scenario, parasite numbers would be controlled as infection progressed; however, even in the absence of cyst formation, low levels of tachyzoites would persist and undergo periodic recrudescence as immune cell numbers declined ( Fig. 4b ). To directly test this prediction, tub1-OVA parasites that lack BFD1 (Δ bfd1 ), a master regulator of tachyzoite to bradyzoite transition 12 , were generated (see Materials and Methods). At 14 dpi, mice infected with wild-type (WT) or Δ bfd1 parasites had comparable parasite burden and T cell responses in the spleen as well as comparable systemic IFN-γ levels ( Extended Data Fig. 3a-c ). In contrast, higher levels of tachyzoite-infected cells were present in the brains of Δ bfd1 -infected mice at 14 and 21 dpi. Interestingly, this was followed by a contraction from 30 to 45 dpi and a recrudescence at 60 dpi ( Fig. 4c ). Fluorescent imaging confirmed that the majority of parasitophorous vacuoles (PVs) in Δ bfd1 -infected mice were negative for dolichos biflorus agglutinin (DBA) which binds the cyst wall, while all PVs in WT-infected mice were DBA + . ( Fig. 4d,e ). A fraction of Δ bfd1 PVs were DBA + , but the DBA staining was weaker than what was seen with WT parasites, and the Δ bfd1 parasites within DBA low vacuoles were Sag1 + (a tachyzoite surface antigen) and SRS9 - (a bradyzoite surface antigen). Conversely, WT parasites within DBA + vacuoles were Sag1 - and SRS9 + ( Extended Data Fig. 3d ). These data confirm that Δ bfd1 parasites do not form cysts in the brain. Download figure Open in new tab Extended Data Fig. 3: WT and Δbfd1 parasites induce comparable immune responses during acute infection. a , Quantification of T. gondii infected cells by flow cytometry in the spleens of mice 14 dpi with tdTomato + WT (black, open circles) or Δbfd1 (red, open squares) parasites. b , Naive CD45.1 + CD45.2 + OT-I T cells were transferred one day prior to infection with WT or Δbfd1 parasites. OT-I T cell frequency and numbers from the spleens of mice at 14 dpi. c , Quantification of serum IFN-γ levels during the course of infection. d , Representative images of T. gondii in the brains of mice 25 dpi with WT (left) or Δbfd1 (right) 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 with 3-5 mice per group. Bar graphs depict the mean ± SD. Data analyzed by two-tailed unpaired Student’s t- test; ns p >0.5. Download figure Open in new tab Fig. 4: Latent stage conversion is not necessary for chronic infection. a, b , Model predicted CNS infection dynamics with or without parasite conversion from tachyzoites to bradyzoites ( c TB ). a , Early dynamics of CNS tachyzoite (I T , red) and bradyzoite (I B , blue) infected cell populations with cyst conversion ( c TB = 0.25, left) or without ( c TB = 0, right). b , Long-term dynamics of tachyzoite infected cell populations in the CNS with c TB = 0.25 (solid line) or c TB = 0 (dashed line). c , Quantification of tdTomato + tachyzoite infected CD45 + leukocytes from the brains of WT (black, open circles) or Δ bfd1 (red, open squares) infected mice, analyzed by flow cytometry. d , Fluorescent imaging of neurons, astrocytes, T. gondii parasites, and cysts in the brains of mice infected with WT (left) or Δ bfd1 (right) parasites at 25 dpi. NeuN, MAP2, and Neurofilament (red); GFAP (cyan); tdTomato + T. gondii (green); Dolichos biflorus agglutinin (DBA, magenta). Scale bar = 10 μm. n=2-4 mice per group, 19-200 vacuoles per mouse. e , Percentage normalization of DBA stained vacuoles at 25 dpi. f, g , Brains of mice infected with WT or Δ bfd1 parasites were analyzed at 6 mpi, after treatment with 200 μg/dose of isotype or α-IFN-γ antibody 2 times/week for 4 weeks prior to harvest. f , Representative photomicrographs of brains from infected mice (H&E). Arrows indicate areas of T. gondii tachyzoite burden. Insets show cysts (upper left) or tachyzoites (lower left and right); IHC for T. gondii. Scale bar = 20 μm. g , Quantification of CNS parasite burden by qPCR. Data are representative of 1-2 independent experiments with 3-5 mice per group. Line graph depicts the mean ± SEM. Bar graphs depict the mean ± SD. Data analyzed by ( c ) 2-way ANOVA or ( e ) two-tailed unpaired Student’s t -test; * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Since cyst formation is considered important for parasite persistence, it was possible that mice which survived infection with Δ bfd1 parasites might fully clear the infection long-term. To determine if cyst formation is required for long-term parasite persistence, the brains of WT-and Δ bfd1 -infected mice that had survived for 6 months were examined. Mice infected with WT parasites exhibited persistent encephalitis, apparent cysts, and detectable levels of parasite DNA by qPCR ( Fig. 4f,g ). In contrast, mice infected with Δ bfd1 parasites lacked overt signs of ongoing inflammation or parasite replication, and parasite burden was below the level of detection by qPCR ( Fig. 4f,g ). However, because IFN-γ limits parasite replication in the CNS 58 , a cohort of mice at 6 mpi were treated with IFN-γ blockade for 4 weeks prior to harvest to determine if this would result in recrudescence. IFN-γ blockade resulted in a marked increase in parasite burden that was apparent by IHC and qPCR in the brains of both WT-and Δ bfd1 -infected mice at 6 mpi. This increase was most prominent in WT-infected brains but was also observed in Δ bfd1 -infected brains ( Fig. 4f,g ). Thus, while cyst formation helps maintain a higher parasite burden in the CNS, it is not essential for long-term persistence of T. gondii . Cyst formation promotes host protection from lethal tachyzoite replication While mice infected with WT or Δ bfd1 parasites had similar rates of survival between 10 and 14 dpi, those infected with Δ bfd1 parasites showed increased mortality between 20 and 40 dpi ( Fig. 5a ). Treatment of Δ bfd1 -infected mice with sulfadiazine (a drug that inhibits tachyzoite replication) starting at 21 dpi rescued mortality ( Fig. 5a ). Histopathological assessment of the brains of Δ bfd1 -infected mice at 30 dpi showed areas of severe tissue necrosis surrounding foci of tachyzoite replication ( Fig. 5b,c ). In contrast, WT-infected brains, despite the presence of inflammation, glial reaction, and cysts, did not exhibit necrosis or remarkable damage to the tissue architecture ( Fig. 5b,c ). Differences in additional indicators of CNS pathology are also apparent in semiquantitative pathological grading of the brains of mice infected with WT and Δ bfd1 parasites ( Extended Data Fig. 5a,b ). Together, these data indicate that higher mortality associated with Δ bfd1 parasites is a consequence of increased levels of tachyzoite replication. Download figure Open in new tab Extended Data Fig. 4: Flow cytometry gating for immune cell populations in the CNS. a , Flow cytometry gating strategy for CNS immune cell populations analyzed in Fig. 5 and Extended Data Figs. 5 and 6 Download figure Open in new tab Extended Data Fig. 5: Immune responses and pathology in the brain during chronic WT and Δbfd1 infection. Brains from naïve mice (grey, open triangles) and mice 30 dpi with WT (black, open circles) or Δbfd1 (red, open squares) parasites were harvested and analyzed. a , Detailed pathological scoring of brain histology sections. b , Cumulative pathology score based on the parameters shown in a . c, d , Flow cytometry analysis of naïve brains and brains at 30 dpi. 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 (black) or Δbfd1 (red) parasites. e , UMAP analysis of OT-I T cells in the brain at 14 and 30 dpi. f , Frequency of CD69 + CD103 + OT-I T cells in the brain at 30 dpi. g , KLRG1 and CX3CR1 expression on OT-I T cells in the brain at 30 dpi. Data are representative of 2-3 independent experiments with 3-5 mice per group. Bar graphs depict the mean ± SD. Data analyzed by ( b ) Mann-Whitney test, ( c, f ) unpaired Student’s t -test; Bonferroni-Dunn correction for multiple comparisons was included in g ; ns p > 0.05, * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. Download figure Open in new tab Fig. 5: Δbfd1 infected mice die of tachyzoite replication despite a competent immune response. a , Survival of mice infected i.p. with WT (black) or Δbfd1 (red) parasites. A subset of mice received sulfadiazine treatment beginning at 21 dpi (WT=blue; Δbfd1 =green). b , Representative photomicrographs of brains from mice infected with WT (left) or Δbfd1 (right) parasites at 30 dpi. Insets show T. gondii cysts in WT infected brains and tachyzoites in Δbfd1 infected brains. H&E; scale bar = 20 μm. c , H&E-stained sections of brain were submitted for assessment and semiquantitative scoring by a board-certified veterinary pathologist. Semiquantitative scores for necrosis severity shown. d , Brain leukocyte cellularity during chronic infection with WT (black, open circles) or Δbfd1 (red, open squares) parasites was quantified by Guava ViaCount Assay. e-h , Flow cytometry analysis of the brains of naive mice (grey) and mice 30 dpi with WT (black) or Δbfd1 (red) parasites. e , UMAP and unsupervised x-shift clustering analysis of CD45 + leukocytes from the brain at 30 dpi. f , Distribution of leukocytes amongst the 8 clusters shown in e . g , Heatmaps displaying MFI of phenotypic markers with the highest expression in cluster 1. h, Quantification of inflammatory monocytes in the brain (CD45 high CD11b + F4/80 + Ly6C hi ). Data are representative of 2-3 independent experiments with 3-20 mice per group. Bar graphs depict the mean ± SD. Data analyzed by ( c ) Mann-Whitney test, ( d ) 2-way ANOVA, ( f ) two-tailed unpaired Student’s t -test with Bonferroni-Dunn correction for multiple comparisons, and ( h ) two-tailed unpaired Student’s t -test; * p < 0.05, ** p < 0.01, *** p < 0.001, and **** p < 0.0001. A possible explanation for increased tachyzoite replication during Δ bfd1 infection could be a reduced immune response in the CNS. However, Δ bfd1 -infected mice had increased numbers of immune cells in the CNS from 20 to 45 dpi compared to WT-infected mice ( Fig. 5d , Extended Data Fig. 5c ). By 60 dpi, CNS immune infiltration in Δ bfd1 -infected mice had contracted to similar levels compared to WT-infected mice, a possible explanation for the resurgence in the number of Δ bfd1 tachyzoite-infected cells shown previously at this timepoint ( Fig. 5d , Fig. 4c ). Phenotyping of the infiltrating immune cells revealed that the overall composition of the CNS immune response at 30 dpi was similar between WT and Δ bfd1 infection ( Fig. 5e,f , Extended Data Fig. 5d ). The only apparent difference in the distribution of CNS immune cell populations was an increase in the proportion and number of inflammatory monocytes (CD45 hi CD11b + F4/80 + Ly-6C hi , cluster 1) during Δ bfd1 infection ( Fig. 5f-h ). Phenotypic analysis was also performed in mice that received OT-I T cells one day prior to infection with WT or Δ bfd1 parasites expressing tub1-OVA. At 14 and 30 dpi OT-I T cells in the brain were phenotypically similar between infections ( Extended Data Fig. 5e ), although at 30 dpi Δ bfd1 infection was associated with a reduction in the CD69 + CD103 + and KLRG1 - CX3CR1 - memory-like populations ( Extended Data Fig. 5f,g ). Thus, the absence of cyst formation was not characterized by any overt loss of immune function. These results suggest that despite the presence of a competent immune response in the CNS, increased levels of tachyzoite replication in the brain during Δ bfd1 infection leads to host mortality. Because the severity of toxoplasmic encephalitis (TE) varies with mouse strain, additional studies were performed in BALB/c mice, which have decreased neuropathology and enhanced repair compared to C57BL/6 mice 59 , 60 . Mortality was not observed in mice infected with either WT or Δ bfd1 parasites ( Extended Data Fig. 6a ). However, BALB/c mice infected with Δ bfd1 parasites showed enhanced immune infiltration, and the majority also showed increased pathology scores and the presence of necrosis in the CNS ( Extended Data Fig. 6b-e ). Additionally, the highest levels of parasite DNA were found in Δ bfd1- infected brains, similar to findings in C57BL/6 mice ( Extended Data Fig. 6f ). These data — in addition to a recent study showing higher tachyzoite burdens in CBA mice infected with a type III strain (VEG) of T. gondii lacking BFD2 14 — highlight that across mouse models of varying resistance to TE, the inability of T. gondii to form cysts is associated with increased levels of tachyzoite replication and associated pathology in the CNS. Download figure Open in new tab Extended Data Fig. 6: 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. Gating scheme to identify populations depicted in Extended Data Fig. 4 . 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) 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 5 mice per group. Bar graphs depict the mean ± SD. Data analyzed by ( b, f ) two-tailed unpaired Student’s t -test or ( c ) Mann-Whitney test; ns p > 0.05, * p < 0.05, ** p < 0.01. Discussion While neurons represent a cellular refuge from the immune system for many pathogens, there is evidence that neurons infected with viruses or T. gondii tachyzoites can be recognized by CD8 + T cells 35 , 43 , 61 . However, the role of CD8 + T cells in control of the latent stage of T. gondii is less well understood. There are reports that depletion of CD8 + T cells in chronically infected mice does not impact cyst numbers, whereas other studies have shown that CD8 + T cells contribute to reduced cyst burden. Perforin-deficient mice have increased cyst numbers, and the transfer of CD8 + T cells from infected mice led to reduced cyst numbers in infected SCID mice in a perforin-dependent manner 41 , 42 , 49 , 62 . In the latter studies, protective CD8 + T cell responses are directed against GRA6, a parasite antigen that is expressed at highest levels in tachyzoites, associated with the intravacuolar membrane, and activates the host transcription factor NFAT 63 , 64 . Because this antigen is expressed in both tachyzoites and bradyzoites, and there are reports that CD8 + T cell recognition of a tachyzoite-expressed model antigen can lead to decreased cyst numbers 43 , it is unclear whether the CD8 + T cell-mediated reduction in cysts is due to control of tachyzoites or direct lysis of neurons that contain cysts. Intravital imaging of the CNS has revealed CD8 + T cells arrested in the vicinity of cysts, but direct interactions with this structure and T cell–mediated lysis of bradyzoite-infected neurons have not been observed 45 – 47 , 54 . Altogether these studies implicate a role for CD8 + T cells in the reduction of T. gondii cysts, but direct evidence of immune responses targeting neuronal cysts has not been shown. 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 the models of host-parasite dynamics in the CNS, suggest that a combination of tachyzoite clearance and bradyzoite-directed immune pressure is required to produce the progressive reduction in cyst numbers that is typical of this infection 21 , 50 . These observations raise new questions about the mechanisms that underlie effector CD8 + T cell recognition of cyst-derived antigens. It is possible that the ability of neurons to upregulate MHC class I allows infected neurons to directly present cyst-derived antigen to CD8 + T cells. Alternatively, periodic cyst reactivation could release cyst-derived antigens and provide the opportunity for cross-presentation by microglia or dendritic cells present in the CNS during TE. Regardless of the mechanism of antigen presentation, we favor a model analogous to some viral systems where local production of IFN-γ provides sustained signals to help neurons control infection 36 , 38 , 39 , 65 . This mechanism of non-cytopathic IFN-γ mediated control may help explain the presence of neurons that had previously been infected with T. gondii but cleared the parasite 66 . Many distinct IFN-γ–mediated anti-microbial mechanisms have been shown to contribute to the control of tachyzoites across cell types and species 67 . However, though immunity-related GTPases have been implicated in the ability of a subset of neurons to clear T. gondii, the relevance of these same mechanisms to bradyzoite control is uncertain 34 . While the focus of this study has been on the mechanisms involved in cyst control, the fact that cysts persist in the presence of immune pressure suggests that this latent stage can either evade IFN-γ–mediated anti-microbial activities or mitigate immune effector responses. Consistent with the former idea are reports that bradyzoites also produce the parasite virulence factor TgIST, which is known to antagonize STAT1 activity upon secretion by tachyzoites 68 – 70 . Expression of this STAT1 antagonist in bradyzoites would suggest that this stage is under selective pressure from IFN-γ. In addition, the finding that the CD8 + T cell response to cyst-derived antigen from bag1-OVA parasites comprises a phenotypically distinct sub-population of CD69 + CD103 + PD1 hi CD8 + T cells was unanticipated. Previous reports have highlighted the presence of a T rm -like population of CD69 + CD103 + CD8 + T cells and expression of PD-1 on CD8 + T cells during TE 45 , 71 , 72 . PD-1 is an inhibitory receptor that limits T cell activation and has been linked to the idea that CD8 + T cells during chronic toxoplasmosis have reduced effector functions 73 . Thus, the PD-1 hi phenotype of the CD8 + T cells responding to bag1-OVA could underlie their reduced ability to produce IFN-γ. Because neurons express low levels of MHC class I, lack costimulatory molecules, and express PD-L1 74 , 75 ; it is possible that class I–restricted CD8 + T cell interactions with infected neurons lead to sub-optimal T cell responses. Decreased effector capacity of T cells responding to infected neurons 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 parasite biology and the host immune response in ways that are not always accessible through experimentation 76 , 77 . Others have noted the lack of tractable models makes it hard to test how latency impacts other pathogens 1 , but the statistical 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 the model parameters ( I B ) or ( ψ T or ψ B ), respectively. This combination of modeling and in vivo experiments provides new insight into the interplay between the latent stage of T. gondii and the host immune response. In particular, the data presented highlight that cyst development provides a replicative sink that tempers tachyzoite expansion in the CNS, mitigating damage to the host. This illustrates the concept that avirulence can be a key feature of the parasitic lifestyle, supported by the existence of defined developmental stages associated with mitigation of virulence across multiple parasites, including Trypanosoma brucei and Schistosomes 78 – 80 . Thus, T. gondii cyst formation in neurons represents a tradeoff between quiescence, which limits parasite replication, and delayed differentiation, which risks damage to the host. Materials and Methods Mice Mice were housed in the University of Pennsylvania vivarium according to institutional guidelines. C57BL/6, CD45.1, Nur77 GFP , OT-I, Stat1 Flox , and BALB/c mice were purchased from Jackson Laboratories and bred at the University of Pennsylvania. Snap25 Cre mice were generously provided by Hongkui Zeng at the Allen Institute for Brain Science. 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. Infections and T cell transfers T. gondii parasites were maintained in culture in human foreskin fibroblasts (HFF). To isolate tachyzoites for infection, T. gondii -infected HFFs were gently scraped from flasks and passed 5 times through a 26G syringe and washed with PBS. Mice were infected by i.p. injection with 5,000-10,000 tachyzoite parasites grown in vitro , unless otherwise stated. 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 i.v. into mice at the indicated timepoint prior to or post-infection. IFN-γ blockade and sulfadiazine treatment In vivo blockade of IFN-γ signaling was performed by i.p. injection of 200 μg per dose of rat IgG1 anti-IFN-γ (clone XMG1.2, BioXcell) or IgG1 anti-horseradish peroxidase for control mice (HRPN, BioXcell). Injections were administered 2 times per week for 4 weeks prior to harvest 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 (DMSO) to 50 mg/mL and added to drinking water at a final concentration of 0.25 mg/mL. Sulfadiazine treated water was administered starting at 21 dpi and refreshed every three days for 4 weeks. Tissue processing and cell counting To generate single cell suspensions for flow cytometry, spleens were passed through a 40μm filter and red blood cells were lysed for 3 minutes at room temperature in ACK lysis buffer. Brains were diced into 1mm pieces and digested at 37C 5% CO 2 for 1.5 hours with 250ug/mL collagenase/dispase and 10μg/mL DNase, and then passed through a 70μm filter. Leukocytes were then isolated through a 30% and 60% percoll gradient and density centrifugation at 2000rpm for 25 minutes. Whole blood was collected through submandibular bleed into 0.05mM EDTA in PBS. Cells were pelleted and red blood cells were lysed for 3 minutes at room temperature in ACK lysis buffer. For quantification of cellularity and live leukocytes isolated from tissues, a fraction of processed cell suspensions were stained with Guava ViaCount Reagent (Cat. No. 11-25209, 240 mL) and analyzed on a Guava easyCyte Flow cytometer according to manufacturer protocol. Generation of transgenic parasites To generate Δ bfd1 parasites, Pru-tub1-OVA-tdTomato parasites were mechanically lysed from host cells by scraping and syringe releasing through a 27G needle. Parasites were pelleted for 10 minutes at 1000g, resuspended in Cytomix (10 mM KPO 4 , 120 mM KCl, 150 mM CaCl 2 , 5 mM MgCl 2 , 25 mM HEPES, 2 mM EDTA), and combined with a DNA transfection mixture to a final volume of 400μl. The final transfection mixture was supplemented with 2 mM ATP and 5 mM glutathione. Two gRNAs contained on a Cas9 expressing plasmid were transfected to target the regions immediately upstream and downstream of the BFD1 locus as previously described 20 . A pTUB-mNeonGreen repair template with homology arms matching the 40 bp regions flanking the cut sites was transfected to allow for sorting of Δ bfd1 parasites by FACS. After sorting, parasites were plated at limiting dilutions to allow for screening of clonal parasites. A Δ bfd1 clone was confirmed by PCR and sanger sequencing. 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. Upstream gRNA sequence: GTTGAGTCCAAGCAGAGCTC Downstream gRNA sequence: GTGTAGAGTCGTGGAAGGAG BFD1 PCR primer forward (to confirm knockout): cctcatccttcgtcacgcgt BFD1 PCR primer reverse (to confirm knockout): tgcttcgggcaggcgactat Generation of bag1 -OVA parasites was performed as described previously 11 : Vectors were generated to contain (i) the bag1 promoter upstream of (ii) the last 31 amino acids of from the T. gondii major glycosyl-phosphatidylinositol-anchored surface antigen, P30, containing the signal sequence for targeting this protein to the parasitophorous vacuole, followed by (iii) amino acids 140-386 of ovalbumin and (iv) a 3’ untranslated region of the dihydrofolate reductase-thymidylate synthase gene. 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 0.01M sodium citrate buffer at pH 6.0, endogenous peroxidase was blocked with 0.3% H 2 O 2 , and sections were blocked with 2% goat serum. Parasites were detected with rabbit anti- T. gondii polyclonal antibody (gifted from Fausto Araujo, Palo Alto Medical Foundation, 1:1000) followed by biotinylated goat anti-rabbit IgG antibody (Vector Laboratories). ABC reagent and DAB substrate (Vector Laboratories) were used according to manufacturer’s protocol to visualize parasite staining, and hematoxylin staining was applied to visualize nuclei. Images were acquired with a Leica DM6000 Widefield Fluorescence Microscope. Pathological Assessment Brains were collected and processed for sectioning as described above. Hematoxylin and eosin-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, hemorrhage, gliosis, necrosis, and presence of parasites) were recorded for individual animals. Flow cytometry Single cell suspensions were plated at up to 2x10 6 cells. Cells were Fc receptor blocked for 20 minutes with 0.5μg/mL αCD16/32 (Clone 2.4G2) and 0.25% normal rat serum in FACs buffer (2% BSA and 0.02mM EDTA in PBS) at 4°C. If staining for tetramer, cells were then washed and incubated with 1:200-1:400 dilution of tetramer in FACs buffer at room temperature for 30 minutes. Following Fc blocking or tetramer stain, surface stain was applied and incubated for 30 minutes 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 minutes 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. Analysis was performed with FlowJo v10.7.2. The following antibodies and reagents were used for staining: B220: BUV496, BD Biosciences: 612950, clone: RA3-6B2, RRID:AB_2870227; CD3: APC-ef780, Invitrogen: 47-0032-82, clone: 17A2, RRID:AB_1272181; CD3: BUV737, BD Biosciences: 612803, clone: 17A2, RRID:AB_2738781; CD3e: PE-cf594, BD Biosciences: 562286, clone: 145-2C11, RRID:AB_11153307; CD4: BUV496, BD Biosciences: 612952, clone: GK1.5, RRID:AB_2813886; CD4: BV650, Biolegend: 100555, clone: RM4-5, RRID:AB_2562529; CD4: FITC, eBioscience: 11-0041-85, clone: GK1.5, RRID:AB_464892; CD4: APC-ef780, Invitrogen: 47-0041-82, clone: GK1.5, RRID:AB_11218896; CD8a: BUV563, BD Biosciences: 748535, clone: 53-6.7, RRID:AB_2872946; CD8a: BUV615, BD Biosciences: 613004, clone: 53-6.7, RRID:AB_2870272; CD8a: BV650, Biolegend: 100742, clone: 53-6.7, RRID:AB_2563056; CD8b: APC-ef780, Invitrogen: 47-0083-82, clone: eBioH35-17.2, RRID:AB_2573943; CD11a: BUV805, BD Biosciences: 741919, clone: 2D7, RRID:AB_2871232; CD11b: BV650, Biolegend: 101259, clone: M1/70, RRID:AB_2566568; CD19: BUV395, BD Biosciences: 563557, clone: 1D3, RRID:AB_2722495; CD45: AF647, Biolegend: 103124, clone: 30-F11, RRID:AB_493533; CD45.1: ef450, Invitrogen: 48-0453-82, clone: A20, RRID:AB_1272189; CD45.1: BV711, Biolegend: 110739, clone: A20, RRID:AB_2562605; CD45.1: PE-Cy7, Biolegend: 110730, clone: A20, RRID:AB_1134168; CD45.2: APC, Biolegend: 109814, clone: 104, RRID:AB_389211; CD45.2: BV711, Biolegend: 109847, clone: 104, RRID:AB_2616859; CD69: BUV737, BD Biosciences: 612793, clone: H1.2F3; CD69: PerCP-Cy5.5, eBioscience: 45-0691-82, clone: H1.2F3, RRID:AB_1210703; CD103: PE, eBioscience: 12-1031-81, clone: 2E7, RRID:AB_11150242; CD103: BV605, Biolegend: 121433, clone: 2E7, RRID:AB_2629724; CD107a: PE-Cy7, Biolegend: 121620, clone: 1D4B, RRID:AB_2562146; CD127: BV421, Biolegend: 135027, clone: A7R34, RRID:AB_2563103; CTLA-4: APC-R700, BD Biosciences: 565778, clone: UC10-4F10-11, RRID:AB_2739350; CX3CR1: BV785, Biolegend: 149029, clone: SA011F11, RRID:AB_2565938; CX3CR1: PerCP-Cy5.5, Biolegend: 149009, clone: SA011F11, RRID:AB_2564493; F4/80: APC-ef780, eBiosciences: 47-4801-82, clone: BM8, RRID:AB_2735036; GFP: AF488, Biolegend: 338008, clone: FM264G, RRID:AB_2563288; H-2Kb: AF647, Biolegend: 116512, clone: AF6-88.5, RRID:AB_492917; I-A/I-E: AF700, Biolegend: 107622, clone: M5/144.15.2, RRID:AB_493727; I-A/I-E: BV711, Biolegend: 107643, clone: M5/144.15.2, RRID:AB_2565976; IFN-γ: BUV737, BD Biosciences: 612769, clone: XMG1.2; Ki-67: BV470, BD Biosciences: 566109, clone: B56, RRID:AB_2739511; KLRG1: BUV395, BD Biosciences: 740279, clone: 2F1, RRID:AB_2740018; Ly-6C: BV785, Biolegend: 128041, clone: HK1.4, RRID:AB_2565852; Ly-6G: BUV563, BD Biosciences: 612921, clone: 1A8, RRID:AB_2870206; NK1.1: BUV395, BD Biosciences: 564144, clone: PK136, RRID:AB_2738618; PD-1: BV421, Biolegend: 135221, clone: 29F.1A12, RRID:AB_2562568; PD-1: BV605, Biolegend: 135220, clone: 29F.1A12, RRID:AB_2562616; PD-1: BV785, Biolegend: 135225, clone: 29F.1A12, RRID:AB_2563680; T-bet: AF647, Biolegend: 644804, clone: 4B10, RRID:AB_1595466; TCRβ: PerCP-Cy5.5, Biolegend: 109228, clone: H57-597, RRID:AB_1575173; TCRβ: ef450, Invitrogen: 48-5961-82, clone: H57-597, RRID:AB_11039532; Tetramer MHCI (OVA): PE, NIH Tetramer Core, peptide: SIINFEKL; Tetramer MHCI (Tgd057): APC, NIH Tetramer Core, peptide: SVLAFRRL; Tetramer MHCII (AS15): APC, NIH Tetramer Core, peptide: AVEIHRPVPGTAPPS; Tim3: BV605, Biolegend: 119721, clone: RMT3-23, RRID:AB_2616907; TNF-α: APC, Invitrogen: 17-7321-82, clone: MP6-XT22, RRID:AB_469508; Vα2 TCR: BUV615, BD Biosciences: 751416, clone: B20.1, RRID:AB_2875415; Vα2 TCR: PE, Biolegend: 127808, clone: B20.1, RRID:AB_1134183; Viability: GhostDye Violet 510, TONBO Biosciences: 13-0870-T100; Viability: GhostDye Red 780, TONBO Biosciences: 13-0865-T100. T cell peptide restimulation Whole splenocytes or brain leukocytes were plated at a constant cell concentration. Cells were incubated with 1μM SIINFEKL (OVA peptide), SVLAFRRL (Tgd057 peptide), or AVEIHRPVPGTAPPS (AS15 peptide) and fluorescently labeled αLAMP1 antibody for 2 hours, followed by a further 2 hours with Protein Transport Inhibitor Cocktail (Invitrogen: 00-4980-03). Cells were analyzed for degranulation and cytokine production by flow cytometry. Fluorescent imaging Brains were harvested from mice following perfusion with heparin in saline followed by 4% paraformaldehyde and stored in 30% sucrose in saline, as described previously 29 . Staining and imaging for neurons, astrocytes, and dolichos biflorus lectin for WT- and Δ bfd1- infected brains was performed as described previously 29 . The following reagents and antibodies were used: DBA (Vector laboratories B1035); GFAP (DAKO Z0334); MAP2 (Abcam ab5392); NeuN (Millipore MAB3778); Neurofilament (Abcam ab4680). SAG1 (DG52) and SRS9 antibodies were gifted by John Boothroyd and used as previously described 81 , 82 . Briefly, 40μm thick sagittal brain sections were generated, stained, and mounted on slides. Images were acquired on a Zeiss LSM 880 inverted confocal microscope (University of Arizona, Imaging Core), images were analyzed using Zen 2.6 blue edition software and counted using ImageJ software. For quantification of cyst size in WT and Stat1 ΔNEU mice, perfused brains were frozen in O.C.T Compound and 10μm sections were cut on a vibratome. Sections were mounted with ProLong Diamond Anti-Fade Mountant with DAPI according to manufacturer’s protocol. Sections were imaged on a Leica SP5-II at 60x magnification. Cysts were defined as vacuoles with >32 parasites present. Cyst area was quantified utilizing Imaris microscopy imaging software and images were generated with LAS AF software. 5-20 vacuoles per brain were quantified. Quantification of serum IFN-γ Blood was collected by submandibular bleed and clotted at room temperature for 1 hour. Serum was separated through centrifugation for 10 minutes at 14,000g. Serum was diluted between 1:5 and 1:20 and IFN-γ levels were assayed by BD Mouse IFN-γ Flex Set Cytometric Bead Array according to manufacturer’s protocol. Beads were analyzed by flow cytometry on a BD Canto. Quantification of parasites by 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. 200ng of DNA was used to quantify parasite burden by qPCR with Power SYBR Green Master Mix and T. gondii specific primers: (forward) 5’-TCCCCTCTGCTGGCGAAAAGT-3’ and (reverse) 5’-AGCGTTCGTGGTCAACTATCGATT G-3’. qPCR was performed on Applied Biosystems ViiA7 with the following conditions: Hold phase 2min 50C, 10min 95C; PCR phase (occurs 50x) 15s at 95C, 1min @60C. Statistical information Statistical tests were run in Prism software (Graphpad). Data were analyzed by two-sided student’s T-tests, two-sided student’s T-tests with Bonferroni-Dunn correction for multiple tests, 2-way analysis of variance (ANOVA), or Mann-Whitney tests where indicated. Not significant p > 0.05; *p<0.05; **p<0.01; ***p<0.001; ****p<0.0001. Data and Code availability All code relating to the generation of ODEs will be made available on github. Author contributions Conceptualization: LAS, CAH, AAK, SL Methodology: LAS, AW, JNE, SC, CJG, EFM, FD Investigation: LAS, JNE, AW, SC, CJG, EFM, EW, DAC, DL, MB, MJ Funding acquisition: LAS, CAH, AAK, EK Supervision: LAS, CAH, AAK, SL, FD, EK Writing – original draft: LAS, CAH Writing – review & editing: CAH, JNE, AW, AAK, SL, SC, EW, DAC, MB, LAS Competing interests The authors do not declare any competing interests. Materials and Correspondence Christopher Hunter; chunter{at}vet.upenn.edu Acknowledgements We thank Anthony T. Phan for assistance with experiments. References 1. ↵ Pirofski , L.-a. & Casadevall , A . The state of latency in microbial pathogenesis . The Journal of Clinical Investigation 130 , 4525 – 4531 ( 2020 ). doi: 10.1172/JCI136221 OpenUrl CrossRef PubMed 2. ↵ Mackowiak , P. A. Microbial latency . Rev Infect Dis 6 , 649 – 668 ( 1984 ). doi: 10.1093/clinids/6.5.649 OpenUrl CrossRef 3. ↵ Munz , C . 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