1. Immunology and Inflammation
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Toxoplasma gondii infection drives conversion of NK cells into ILC1-like cells

  1. Eugene Park
  2. Swapneel Patel
  3. Qiuling Wang
  4. Prabhakar Andhey
  5. Konstantin Zaitsev
  6. Sophia Porter
  7. Maxwell Hershey
  8. Michael Bern
  9. Beatrice Plougastel-Douglas
  10. Patrick Collins
  11. Marco Colonna
  12. Kenneth M Murphy
  13. Eugene Oltz
  14. Maxim Artyomov
  15. L David Sibley
  16. Wayne M Yokoyama  Is a corresponding author
  1. Washington University School of Medicine, United States
  2. ITMO University, Russia
  3. Ohio State University Wexner School of Medicine, United States
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Cite this article as: eLife 2019;8:e47605 doi: 10.7554/eLife.47605

Abstract

Innate lymphoid cells (ILCs) were originally classified based on their cytokine profiles, placing natural killer (NK) cells and ILC1s together, but recent studies support their separation into different lineages at steady-state. However, tumors may induce NK cell conversion into ILC1-like cells that are limited to the tumor microenvironment and whether this conversion occurs beyond this environment remains unknown. Here, we describe Toxoplasma gondii infection converts NK cells into ILC1-like cells that are distinct from both steady-state NK cells and ILC1s in uninfected mice. These cells were Eomes-dependent, indicating that NK cells can give rise to Eomes Tbet-dependent ILC1-like cells that circulate widely and persist independent of ongoing infection. Moreover, these changes appear permanent, as supported by epigenetic analyses. Thus, these studies markedly expand current concepts of NK cells, ILCs, and their potential conversion.

https://doi.org/10.7554/eLife.47605.001

Introduction

Innate lymphoid cells (ILCs) comprise diverse populations. Like T and B cells, they are derived from common lymphoid progenitors (CLPs) but do not undergo antigen receptor recombination (Spits and Cupedo, 2012). ILCs are tissue-resident within mucosal sites where they participate in tissue homeostasis and survey for pathogens (Sojka et al., 2014a; Gasteiger et al., 2015), although recent studies showed that inflammation can induce ILC2 mobilization (Huang et al., 2018). ILC classification was initially based on their cytokine production, with type 1 ILCs (ILC1s) producing IFNγ, ILC2s producing IL-5 and IL-13, and ILC3s producing IL-17 and IL-22. ILC classification was subsequently corroborated by distinctive markers and developmental requirements.

Prior to the discovery of ILCs, NK cells were the only known innate CD3 lymphocytes. Their classification within the larger scheme of ILCs has been challenging, in particular due to their strong resemblance to ILC1s while also maintaining important distinctions. For example, mouse ILC1s and NK cells both express NK1.1 and NKp46 and produce IFNγ, and as such were initially classified together as Group 1 ILCs (Spits et al., 2013). However, grouping NK cells with ILC1s was confounded by several discordant features. Whereas ILC1s are restricted to organs, and CD49a expression is a faithful marker of tissue-resident populations under steady-state conditions (Peng et al., 2013; Sojka et al., 2014a), most NK cells freely circulate. These cells also differ in their developmental requirements, with NK cells requiring Eomes for development, while Eomes is not expressed in ILC1s and is dispensable for development (Daussy et al., 2014). Moreover, ILC1s are completely Tbet-dependent (Daussy et al., 2014; Sojka et al., 2014a), whereas NK cells require Tbet only for maturation (Townsend et al., 2004; Gordon et al., 2012). Consistent with their differential requirements for T-box transcription factors, NK cells and ILC1s arise at different branch points downstream of the CLP. While NK cells originate from NK cell precursor cells (Rosmaraki et al., 2001), other ILCs further differentiate along a pathway that includes the common helper innate lymphoid progenitor (CHILP) and ILC precursor (ILCP), which do not have NK cell potential (Klose et al., 2014; Constantinides et al., 2014; Yang et al., 2015). Given the many ways in which NK cells and ILC1s differ, ILC classification was recently revised so that NK cells and ILC1s are now considered distinct ILC lineages (Vivier et al., 2018).

Constructing clear definitions of NK cells and ILC1s is complicated, however, by their plasticity and heterogeneity upon stimulation, which can alter the features that discriminate between them under steady state conditions. For example, within the tumor microenvironment or upon in vitro culture with TGF-β, NK cells may downregulate Eomes and resemble ILC1s (Gao et al., 2017; Cortez et al., 2016). However, these cells are found only in the tumor microenvironment in vivo and it is not clear if they can persist in the absence of tumor. Moreover, NK cells and ILC1s become activated under similar circumstances, such as murine cytomegalovirus (MCMV) infection and tumorigenesis (Weizman et al., 2017; Dadi et al., 2016; Yokoyama, 2013). As it is currently difficult to assess NK cells independently of ILC1s, changes undergone by either population may be masked by the presence of the other. Independent examination of each population, especially in settings known to stimulate NK cells and ILC1s, is required to better understand these cells and their relationship to each other.

Both NK cells and ILC1s respond to infection with Toxoplasma gondii, an intracellular parasite that infects a third of the global population and is a natural pathogen in mice (Montoya and Liesenfeld, 2004). During acute infection, rapidly replicating tachyzoites disseminate systemically, triggering dendritic cells to produce IL-12, which subsequently stimulates NK cells to produce IFNγ and ILC1s to produce IFNγ and TNFα (Klose et al., 2014; Goldszmid et al., 2012). Tachyzoites eventually differentiate into slowly replicating bradyzoites, which are primarily encysted within cells of the central nervous system and skeletal muscle (Yarovinsky, 2014). As T. gondii infection elicits activation of both NK cells and ILC1s, herein we sought to investigate how NK cells and ILC1s respond to gain better insight into inflammation-induced changes. Indeed, we found that ILC1s become permanently heterogeneous after infection, largely owing to the surprising conversion of NK cells into ILC1-like cells.

Results

T. gondii infection results in expansion of ILC1-like cells

Following administration of anti-NK1.1, acute infection with the type II Prugniaud (Pru) strain of T. gondii resulted in increased parasite load and higher mortality rates as compared to isotype control-treated mice (Figure 1—figure supplement 1A–C), consistent with previous reports (Goldszmid et al., 2007). Since anti-NK1.1 affects both NK cells and ILC1s and both have been previously implicated in the immune response to T. gondii (Goldszmid et al., 2012; Klose et al., 2014), we sought to investigate how NK cells and ILC1s respond to infection. Here, we assessed these populations by following expression of Eomesodermin (Eomes) and CD49a among CD3 CD19 NK1.1+ NKp46+ cells, as NK cells express Eomes and not CD49a while ILC1s express CD49a but not Eomes at steady-state. In the uninfected spleen, the vast majority of NK1.1+ NKp46+ cells were NK cells (Figure 1A). There was a small population of spleen cells resembling ILC1s in uninfected mice, even though ILC1s are primarily found in other organs including the liver and small intestine and are generally tissue-resident (Sojka et al., 2014a; Fuchs et al., 2013), whereas cells in the spleen are generally circulating cells (Gasteiger et al., 2015; Sojka et al., 2014a; Peng et al., 2013). Interestingly, over the course of infection, NK cells decreased both as a proportion of NK1.1+ NKp46+ cells and in absolute number (Figure 1A,B). By contrast, there was an increase in cells resembling ILC1s that was clearly evident at 21-day post-infection (p.i.) (Figure 1A,C). Since ILC1 markers were established for ILC1s in uninfected mice, we have termed these cells resembling ILC1s as ‘ILC1-like cells.’ Notably, ILC1-like cells from infected mice mostly expressed Ly6C (Figure 1A,D), a marker that correlates with NK cell maturity (Omi et al., 2014) and is expressed by MCMV-induced memory NK cells (Sun et al., 2012) and is not expressed by the vast majority of ILC1-like cells present in the spleen under steady-state conditions. The expansion of splenic ILC1-like cells persisted for at least 4 months p.i. (Figure 1E).

Figure 1 with 1 supplement see all
T. gondii infection results in expansion of ILC1-like cells.

(A–E) Wild-type mice were infected by i.p. injection of 200 tachyzoites of the Prugniaud (Pru) strain of T. gondii. Splenocytes were analyzed at indicated time points p.i. (A) Representative flow cytometry plots for the analysis of NK cells (Eomes+ CD49a) and ILC1-like cells (Eomes CD49a+), and Ly6C expression by NK cells and ILC1-like cells, at indicated time points p.i., among CD3 CD19– NK1.1+ NKp46+ cells. (B,C) Frequency and absolute number of NK cells (B) and ILC1-like cells (C) from spleens of uninfected mice and mice at indicated time points p.i. Numbers derived from gates indicated in (A), n = 5 mice. (D) Frequency of ILC1s that express Ly6C at indicated time points p.i., n = 5 mice. (E) Representative flow cytometry plots for the analysis of NK cells and ILC1-like cells, and their frequency and absolute number four mo p.i., n = 6 mice (uninfected) or n = 7 mice (infected). Mean + s.e.m (B–E); one-way ANOVA with Bonferroni correction (B–D); unpaired t-test (E); *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001. Data are representative of 5 independent experiments.

https://doi.org/10.7554/eLife.47605.002

ILC1-like cell expansion persists in the absence of ongoing infection

Two major possibilities could account for the sustained expansion of ILC1-like cells. They may represent a response to ongoing parasite replication, as bradyzoites develop following acute infection with Pru T. gondii infection and parasite reactivation can occur. Alternatively, the increased ILC1-like cells might represent a permanent change that persists even after infection subsides. To test whether ongoing parasite replication plays a role, we infected mice with T. gondii, then suppressed growth of tachyzoites with sulfadiazine at various time points p.i. (Eyles and Coleman, 1955). Interestingly, infection-induced expansion of ILC1-like cells, as seen at 35 d.p.i, even in sulfadiazine-treated mice when treatment began 7 or 10 d.p.i., with cell numbers comparable to those of untreated, infected mice (Figure 2A). ILC1-like cell expansion also occurred following repeated administration of the Cps1-1 T. gondii strain (Figure 2B), which does not replicate in vivo and therefore does not persist in a chronic form (Fox and Bzik, 2002). Moreover, the number of ILC1-like cells was similar after infection with a single inoculum of Δgra4 parasites, which are defective in cyst formation (Fox et al., 2011; Jones et al., 2017), as compared to the WT parental Pru strain (Figure 2C). BALB/c mice, which have fewer cysts during chronic T. gondii infection (Suzuki et al., 1993), also had increased numbers of ILC1-like cells after Pru infection (Figure 2D), also indicating that expanded ILC1-like cells were not confined to infected C57BL/6 mice. In summary, we found that T. gondii infection induced expansion of ILC1-like cells, which persisted independent of ongoing parasite replication, suggesting a permanent change; in subsequent experiments, we further examined the impact of infection with the Pru strain of T. gondii.

ILC1-like cell expansion persists in the absence of ongoing infection.

(A–D) Representative flow cytometry plots for the analysis of NK cells (Eomes+ CD49a) and ILC1-like cells (Eomes CD49a+), and frequency and absolute number of ILC1-like cells in the spleen following (A) treatment with sulfadiazine (SDZ) beginning at indicated time points p.i. and maintained on sulfadiazine until 35 d p.i. when they were analyzed, n = 5–11 mice; (B) injection with 1 × 105 tachyzoites three times, two wk apart, and analyzed 42 d after initial injection, n = 4 mice (uninfected) or n = 5 mice (Cps1-1); (C) infection with PruΔku80 (WT) and PruΔku80Δgra4 (Δgra4) T. gondii analyzed 35 d.p.i., n = 8 mice (WT) or n = 10 mice (Δgra4); (D) infection of BALB/c mice 35 d.p.i., n = 3 mice. Mean + s.e.m (A–D); one-way ANOVA with Bonferroni correction (B); unpaired t-test (B–D); ns not significant, *p≤0.05, **p0.01, ***p≤0.001, ****p≤0.0001. Data are representative of three independent experiments.

https://doi.org/10.7554/eLife.47605.004

Expansion of ILC1-like cells among circulating cells

ILC1s have previously been established as being tissue-resident under steady state conditions (Gasteiger et al., 2015; Sojka et al., 2014a; Peng et al., 2013). Surprisingly, however, we found that infected mice displayed ILC1-like cell expansion even in the blood, and a highly vascularized organ, that is the lung, indicating that at least some of these cells circulate (Figure 3A,B). Consistent with our previous findings in the spleen (Figure 1A,D), ILC1-like cells in the blood and lungs of infected mice also expressed Ly6C (Figure 3—figure supplement 1A). However, there was no increase of ILC1-like cells in the mesenteric lymph node, brain, peritoneum, bone marrow, uterus, or salivary gland (Figure 3C, Figure 3—figure supplement 1B). Nonetheless, these data indicated that T. gondii infection induced ILC1-like cell expansion, even in the circulation.

Figure 3 with 1 supplement see all
Expansion of ILC1-like cells among circulating cells.

(A) Representative flow cytometry plots for the analysis of NK cells and ILC1-like cells in the blood and lung of uninfected and d35-infected mice. (B) Absolute number of ILC1-like cells in the blood and lung of uninfected and d35 infected mice. (C) Frequency of ILC1-like cells among NK1.1+ NKp46+ cells in indicated organ at 35 d.p.i., n = 3 mice (uninfected) or n = 5 mice (infected). Mean + s.e.m (A,C); unpaired t-test; ns not significant, *p≤0.05, ***p≤0.001, ****p≤0.0001. Data are representative of three independent experiments.

https://doi.org/10.7554/eLife.47605.005

Parabiosis experiments could provide supportive evidence of circulating versus tissue-resident cells, but the possible reactivation and spread of T. gondii following surgery, as seen clinically (Bosch-Driessen et al., 2002), could confound analysis. Instead, we utilized Eomes-GFP reporter mice to assess how ILC1-like cells and NK cells from spleens of infected mice behave following transfer into uninfected mice (Daussy et al., 2014). We isolated NK cells and ILC1-like cells from congenically distinct Eomes-GFP mice 35 d.p.i. for adoptive transfer into naive Rag2-/-Il2 rg-/- mice (Figure 4A). When we assessed the recipient mice 24 days later, we detected both transferred populations in the spleen and liver, though there was a much smaller percentage of transferred NK cells in the liver (Figure 4B). Although NK cells upregulated CD49a upon transfer into Rag2-/-Il2 rg-/- mice, as previously reported (Gao et al., 2017), Eomes expression remained high in most transferred NK cells, compared to most transferred ILC1-like cells which remained Eomes (Figure 4C). Interestingly, following adoptive transfer of ILC1-like cells, some Eomes cells recovered from the spleen expressed Eomes (Figure 4C), suggesting that in certain contexts, Eomes ILC1-like cells may give rise to Eomes+ cells, similar to what has been shown previously for ILC1s (Gordon et al., 2012; Takeda et al., 2005). Therefore, in the setting of homeostatic expansion, most transferred NK cells and ILC1-like cells from infected mice persist with generally stable Eomes expression, and transferred ILC1-like cells from infected mice circulate, providing complementary evidence, in addition to above (Figure 2A–D), that they persist in the absence of ongoing infection.

Delineation of NK cells, ILC1s, and ILC1-like cells in the liver.

(A) Overview of competitive transfer experiment. At 35 d.p.i., Eomes-GFP+ CD49a and Eomes-GFP CD49a+ cells were sorted from the spleens of CD45.2 and CD45.1 x CD45.2 Eomes-GFP reporter mice, respectively. Cells were combined in a 1:1 ratio and intravenously injected into Rag2-/-Il2rg-/- mice. 24 days later, spleens and livers of recipients were assessed for transferred cells. (B) Representative flow cytometry plots of CD45.1 and CD45.2 expression by transferred cells in the spleen and liver of Rag2-/-Il2rg-/- mice, and frequency of transferred NK cells (CD45.2+) and ILC1s (CD45.1+ CD45.2+) 24 days post-transfer, as described in (A), n = 5 mice. (C) Representative flow cytometry plots of Eomes-GFP and CD49a expression by transferred NK cells and ILC1-like cells in the spleen (top) and liver (bottom) of Rag2-/-Il2rg-/- mice, and frequency of Eomes CD49a+ 24 days post-transfer, as described in (A) n = 5 mice. (D) Representative flow cytometry plots for the analysis of CD49a and Eomes among CD3 CD19 NK1.1+ NKp46+ cells, and Ly6C expression by Eomes+ CD49a, Eomes+ CD49a+, and Eomes CD49a+ cells in the liver at indicated time points p.i. (E,F) Frequency and absolute number of CD3 CD19 NK1.1+ NKp46+ cells that are Eomes+ CD49a, Eomes+ CD49a+, and Eomes CD49a+ in the livers of uninfected and d35-infected mice, n = 3 mice (uninfected) or n = 5 mice (infected). (G) Frequency of Ly6C+ cells among CD3 CD19 NK1.1+ NKp46+ Eomes+ CD49a, Eomes+ CD49a+, and Eomes CD49a+ cells in the livers of d35-infected mice, n = 3 mice. (H) Frequency of CD3 CD19 NK1.1+ NKp46+ cells that are Eomes CD49a+ (ILC1 and ILC1-like) and express Ly6C, and absolute number of Ly6C+ ILC1-like cells and Ly6C ILC1s from livers of uninfected and d35-infected mice, n = 3 mice (uninfected) or n = 5 (infected). Mean + s.e.m. (B,C,E–H) unpaired t-test (B,C,E,F,H) one-way ANOVA with Bonferroni correction (G); ns not significant, *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001. Data are representative of 3 independent experiments.

https://doi.org/10.7554/eLife.47605.007

Interestingly, however, the ratio of transferred ILC1-like cells to NK cells was higher in the liver than in the spleen, with ILC1-like cells comprising nearly all transferred cells in the liver (Figure 4B). This suggested that the ILC1-like cells from infected mice may not uniformly circulate and rather they might preferentially migrate to the liver despite originating in the spleen. Alternatively, the adoptive transfer studies may be revealing properties of heterogeneous populations of cells. To further evaluate these issues, we studied the liver, which contains a large population of ILC1s in uninfected mice (Sojka et al., 2014a; Peng et al., 2013), in more detail directly following primary infection. Infection decreased the frequency of liver NK cells among NK1.1+ NKp46+ cells, although the total NK cell number did not change (Figure 4D–F). Notably, we observed that infection resulted in a striking population of liver Eomes+ CD49a+ cells (Figure 4D–F). The frequency and absolute number of ILC1s also did not change (Figure 4D–F). We examined Ly6C expression by Eomes+ CD49a, Eomes+ CD49a+, and Eomes CD49a+ cells in the infected liver and found that Ly6C was expressed most highly by Eomes CD49a+ cells after infection (Figure 4D,G), and to a lesser extent by Eomes+ CD49a+ cells. Interestingly, Ly6C was expressed at a higher percentage by cells with an ILC1 phenotype (Eomes CD49a+) in the infected spleen (~80%, Figure 1D) than in the infected liver, where only half of such cells expressed Ly6C (Figure 4H), suggesting heterogeneity among liver cells resembling ILC1s. Accordingly, the number of liver Ly6C+ ILC1-like cells (Eomes CD49a+) was increased relative to uninfected mice, whereas the number of Ly6C ILC1s (Eomes CD49a+) remained comparable (Figure 4H), suggesting that at 35 d.p.i. Ly6C expression may distinguish between steady-state ILC1s and ILC1-like cells induced by infection. Taken together, the data suggest that in infected mice, steady-state ILC1s are maintained while an additional ILC1-like subset arises and circulates.

ILC1-like cells are distinct from NK cells and ILC1s

Ly6C is expressed by ILC1-like cells in the spleen, blood, and liver of infected mice, suggesting that T. gondii induces ILC1-like cells that are rare under steady-state conditions. To assess the possibility of a novel ILC1-like subset, we first performed more detailed comparisons of NK cells and ILC1-like cells in the spleens of uninfected and infected mice. As circulatory capacity was specific to ILC1-like cells in infected mice, we examined expression of molecules typically associated with ILC1 tissue-residency (Sojka et al., 2014a; Daussy et al., 2014). ILC1-like cells in both uninfected and infected mice did not express CD62L and expressed higher levels of PECAM-1 and CXCR6 compared to NK cells (Figure 5A). However, infection resulted in NK cells and ILC1-like cells gaining expression of CCR8 and CX3CR1 compared to NK cells and ILC1s in uninfected mice. We also assessed expression of DNAM-1 and KLRG1, which correlate with the maturational state of NK cells (Goh and Huntington, 2017). We found that ILC1-like cells from infected mice expressed DNAM-1 more highly than NK cells, and KLRG1 at higher levels than NK cell or ILC1 populations (Figure 5B). We also observed that T. gondii-induced ILC1-like cells were unique in their expression of Neuropilin-1, a cell surface protein involved in activation of regulatory T cells (Sarris et al., 2008), but not previously described in NK cells or ILC1s.

Figure 5 with 2 supplements see all
ILC1-like cells are distinct from NK cells and ILC1s.

(A,B) Representative flow cytometry plots showing expression of indicated markers by indicated cells from spleens of uninfected and d35-infected mice, and frequency of each cell population that expresses each marker, n = 3 mice (A) uninfected) or n = 5 mice (A) infected and B). (C,D) Representative flow cytometry plots and frequency of indicated cells in uninfected and d35-infected mice after 4 hr culture with indicated stimulus that contain intracellular IFNγ (C) or TNFα (D), n = 5. Mean + s.e.m. (A–D) one-way ANOVA with Bonferroni correction (A–D); *p≤0.05, **p≤0.01, ***p≤0.001, ****p≤0.0001, in comparisons of ILC1-like cells from infected mice with the NK cells in infected mice, and the ILC1s in uninfected mice. When these comparisons were not significant, the comparison is not shown. Data are representative of three independent experiments.

https://doi.org/10.7554/eLife.47605.008

NK cell development is classically described as a stepwise maturation process through CD27 CD11b, CD27+ CD11b, CD27+ CD11b+, and CD27 CD11b+ stages (Chiossone et al., 2009), while ILC1s do not undergo these stages and are primarily CD27+ CD11b (Sojka et al., 2014a). In the spleen, we found that ILC1s from uninfected mice were predominantly CD27+ CD11b and NK cells from uninfected and infected mice encompassed all subsets (Figure 5—figure supplement 1A), as previously shown. However, ILC1-like cells from infected mice were mainly CD27 CD11b+ (Figure 5—figure supplement 1A). With respect to NK cell receptor expression, ILC1-like cells from infected mice resembled ILC1s from uninfected mice, expressing NKG2A and low frequencies of Ly49 receptors (Figure 5—figure supplement 1B). Regarding cytokine production, NK cells and ILC1s in both uninfected and infected mice produced IFNγ in response to stimulation (Figure 5C), a hallmark of both cell types (Sojka et al., 2014b). Similarly, ILC1-like cells also produced IFNγ. However, only ILC1s from uninfected mice produced TNFα (Figure 5D). Similar results were obtained from studies of ILC1-like cells in blood of infected mice (Figure 5—figure supplement 1C,D). Thus, the spleens and blood of infected mice contained a novel ILC1-like subset.

Studies of the infected liver solidified the notion that infection induced a distinct ILC1-like subpopulation. In the liver, we separately assessed the Ly6C ILC1s that are present in uninfected mice, as well as both Ly6C ILC1s and Ly6C+ ILC1-like cells in infected mice (Figure 5—figure supplement 2A). Ly6C+ ILC1-like cells expressed higher levels of CX3CR1, Neuropilin-1, KLRG1, and CD11b, lower levels of CXCR6 and CD27, and produced less TNFα than Ly6C ILC1s in uninfected and infected mice, which were similar (Figure 5—figure supplement 2B–D). Therefore, the Ly6C+ ILC1-like cells in the liver therefore resembled those in the infected spleen (Figure 5A–D, Figure 5—figure supplement 1A,B), suggesting that while ILC1s in uninfected mice and ILC1-like cells in infected mice share the Eomes CD49a+ phenotype, they can be distinguished by marker expression and cytokine production profile.

T. gondii infection induces heterogeneity of NK cells and ILC1s

ILC1-like cells from spleens of infected mice expressed high levels of Tbet (Figure 6A), which was previously identified as a requirement for ILC1 development (Daussy et al., 2014; Sojka et al., 2014a). We therefore hypothesized that Tbet may be required for ILC1-like cell expansion after infection. As Tbx21-/- mice succumb to T. gondii infection (Harms Pritchard et al., 2015), we studied WT:Tbx21-/- mixed bone marrow chimeras. In spleens of both uninfected and infected chimeras, NK cells were present though they were biased towards WT origin (Figure 6—figure supplement 1A), consistent with a requirement for Tbet to complete NK cell maturation (Gordon et al., 2012). However, no ILC1-like cells (Eomes CD49a+) were found of Tbx21-/- origin in infected WT:Tbx21-/- chimeras, as with ILC1s in naive chimeras (Figure 6B). Thus, splenic ILC1-like cells are Tbet-dependent.

Figure 6 with 1 supplement see all
T.gondii infection induces heterogeneity of NK cells and ILC1s.

(A) Representative flow cytometry plots showing Tbet expression by indicated cells from spleens of uninfected and d35-infected mice, and gMFI of Tbet expression by each population, n = 3 mice (uninfected) or n = 5 mice (infected). (B) Representative flow cytometry plots for the CD49a and Eomes expression among CD3 CD19 NK1.1+ NKp46+ cells of CD45.1-derived (WT) or CD45.2-derived (Tbx21-/-) cells from spleens and livers of uninfected and d35-infected WT:Tbx21-/- bone marrow chimeras, and frequency of Eomes+ CD49a+ cells from spleen and liver, n = 4 mice (uninfected) or n = 7 mice (infected). In right panel, KO cells indicated by open bars. (C) Biaxial t-SNE analysis of cells pooled across all samples. Points represent individual cells, colors denote different clusters. (D) Biaxial t-SNE analysis of cells in individual samples. (E) Fraction of cells in C1-C17 within each sample. (F) Heatmap of average expression of select genes that are characteristic of C1-C17. (G) Expression of indicated genes by cells in each sample. Mean + s.e.m. (A,B); one-way ANOVA with Bonferroni correction (A,B); ns not significant *p≤0.05, **p≤0.01, ****p≤0.0001; data are representative of three independent experiments (A–C).

https://doi.org/10.7554/eLife.47605.011

In the livers of infected WT:Tbx21-/- chimeras, the picture was more complex. There were no ILC1s (Eomes CD49a+) of Tbx21-/- origin in the infected liver, as with infected spleens (Figure 6B). However, the livers of infected WT:Tbx21-/- chimeras displayed an accumulation of Tbx21-/- Eomes+ CD49a+ cells that were not present in the spleen (Figure 6B). Eomes+ CD49a+ cells were also present among counterpart WT cells, though at lower frequencies. These data suggested that ILC1-like cells in infected mice may be derived from Eomes+ cells, that is, NK cells.

To better assess the heterogeneity induced by T. gondii infection and the role of Tbet in this process, we performed single-cell RNA-seq (scRNA-seq) on sorted WT (CD45.1+) or Tbx21-/- (CD45.2+) NK1.1+ NKp46+ cells from uninfected and d35-infected WT:Tbx21-/- chimeras. We chose to examine the liver for this analysis for several reasons: 1) infection appears to induce a novel ILC1-like subset that is common to the liver and spleen; 2) the liver contains ILC1s under steady-state, allowing for direct comparison of steady-state ILC1s and T. gondii-induced ILC1-like cells; and 3) the infected liver uniquely contains a Tbx21-/- Eomes+ CD49a+ population. Using t-distributed stochastic neighbor embedding (t-SNE) analysis, we grouped the cells into 17 clusters, C1-C17 (Figure 6C). In the uninfected WT sample, C1 was the largest cluster, whereas C1 was diminished in the infected WT and Tbx21-/- samples (Figure 6D,E). C1 cells expressed Eomes and Itgam but did not express Cd27 or Itga1 (Figure 6F,G), consistent with C1 being mature NK cells, which are indeed the predominant NK1.1+ NKp46+ cells present in the steady-state liver (Figure 6—figure supplement 1B–D). C3 was the second largest cluster in the uninfected WT sample, and C3 cells did not express Eomes or Ly6c2, expressed Itga1, Cd27, and Cxcr6, and were absent in Tbx21-/- samples, indicating that C3 comprised ILC1s (Figure 5F,G, Figure 6—figure supplement 1D).

Two closely related clusters, C10 and C11, were unique to the infected WT sample (Figure 6D,E). Cells in C10 and C11 expressed Itga1, Ly6c2, and Klrg1, and did not express Eomes (Figure 6F,G). This specificity to infection, Tbet-dependence, and gene expression identified these cells as T. gondii-induced ILC1-like cells. Interestingly, these two clusters indicated heterogeneity even within the T. gondii-induced ILC1-like population. The t-SNE analysis placed C10 closer to mature NK cells (C1) and C11 closer to ILC1s (C3). Comparison of C10 and C11 revealed that C10 expressed signature NK cell genes at higher levels (Robinette et al., 2015), whereas C11 expressed higher levels of signature ILC1 genes (Figure 6—figure supplement 1E). Interestingly, C10 also highly expressed Cx3cr1 whereas C11 did not (Figure 6F,G). We corroborated these findings with flow cytometric analysis that showed that Ly6C+ ILC1-like cells in the infected liver contained both a CX3CR1+ CXCR6 population that expressed higher levels of Zeb2, mirroring the C10 phenotype, and also a CX3CR1 CXCR6+ population that mirrors C11 (Figure 6—figure supplement 1F,G). Furthermore, C10 expressed lower levels of Il7ra than C3 and C11 (Figure 6F). As IL-7 receptor signaling is required for ILC1 development but not for NK cells (Klose et al., 2014), this finding is suggestive of discrete developmental origins of C10 and C11, which we further discuss below. C5 was also increased in the infected samples, and these cells co-expressed Eomes and Itga1, and were especially prominent in the infected Tbx21-/- sample (Figure 6E,G), suggesting that this cluster includes the Eomes+ CD49a+ cells that arose in the liver after infection (Figures 4E and 6B). In summary, scRNA-seq analysis revealed that T. gondii infection induces heterogeneous NK cell and ILC1 populations, including two distinct ILC1-like subpopulations that are unique to infected mice.

NK cells downregulate Eomes during T. gondii infection

scRNA-seq analysis revealed heterogeneity of NK1.1+ NKp46+ cells and showed that some T. gondii-induced ILC1-like cells have core NK cell traits. To assess if NK cell conversion into ILC1-like cells might account for this population by means of Eomes downregulation, we examined Ncr1iCre Eomesf/f (Eomes conditional KO or cKO) mice, in which NK cells are absent owing to their requirement for Eomes, as shown by a drastic reduction of NK1.1+ NKp46+ cells (Figure 7—figure supplement 1A). Meanwhile, the number of CD49a+ ILC1s is unaffected while the frequency of these cells among CD3 CD19 NK1.1+ NKp46+ cells is increased due to the absence of NK cells (Figure 7A,B) (Gordon et al., 2012; Pikovskaya et al., 2016). Following T. gondii infection, the numbers of CD49a+ and CD49a+ Ly6C+ cells in the spleen were significantly reduced in Eomes cKO compared to Eomesf/f controls (Figure 7A,B), showing that expansion of these cells requires Eomes. However, while the overall number of CD49a+ cells did not change between uninfected and infected Eomes cKO mice, the number of CD49a+ Ly6C+ cells increased slightly (Figure 7B), and a greater frequency of the CD49a+ cells expressed Ly6C (Figure 7C), showing that mild ILC1 expansion occurs in the absence of NK cells (indicated by bracket). However, approximately three times as many CD49a+ Ly6C+ cells were derived from Eomes-dependent cells, that is, NK cells (Figure 7B, indicated by bracket), suggesting Eomes expression by NK cells contributes to the development of most ILC1-like cells.

Figure 7 with 1 supplement see all
Most ILC1-like cells are derived from NK cells during T.gondii infection.

(A) Representative flow cytometry plots for the analysis of ILC1s (CD3 CD19 NK1.1+ NKp46+ CD49a+) or ILC1-like cells (CD3 CD19 NK1.1+ NKp46+ CD49a+ Ly6C+), and (B) absolute number of these cells in the spleens of Eomesf/f and Eomes cKO mice that are uninfected and at 35 d.p.i., n = 7 mice (uninfected Eomesf/f), n = 8 mice (infected Eomesf/f), n = 7 mice (uninfected cKO), or n = 9 mice (infected cKO). The increased number of CD49a+ Ly6C+ cells in infected versus uninfected Eomesf/f mice represent both NK cells and ILC1 origin, whereas in cKO mice, the increased number represents ILC1 origin only, as indicated by the brackets. (C) Representative flow cytometry plot showing expression of Ly6C and frequency of ILC1s that express Ly6C, n = 7 mice (uninfected Eomesf/f), n = 8 mice (infected Eomesf/f), n = 7 mice (uninfected cKO), or n = 9 mice (infected cKO). (D) Representative flow cytometry plots for the analysis of chimerism in the spleens of uninfected and d35-infected WT:Eomesf/f and WT:Eomes cKO bone marrow chimeras, and frequency of ILC1s that are derived from WT, Eomesf/f, or Eomes cKO bone marrow, n = 4 mice (uninfected) or n = 5 (infected). (E) Representative flow cytometry plots for the analysis of chimerism in the spleens of uninfected and d35-infected WT:Stat4-/- bone marrow chimeras, and frequency of NK cells and ILC1-like cells that are derived from WT or Stat4-/- bone marrow, n = 3 mice. Mean + s.e.m. (B–D); one-way ANOVA with Bonferroni correction (B–D); ns not significant *p≤0.05, **p≤0.01, ****p≤0.0001. Data are representative of three independent experiments.

https://doi.org/10.7554/eLife.47605.013

The role of Eomes-expressing NK cells in formation of T. gondii-induced ILC1-like cells could be either cell-intrinsic or cell-extrinsic. Although an Eomes fate-mapping mouse, that is, EomesCre, could be used to identify a cell-intrinsic role for Eomes, this was not possible due to the ubiquitous expression of Eomes during development (data not shown). Another approach would be to examine Eomes downregulation following adoptive transfer of congenic NK cells prior to infection but this was hindered due to the inability to find transferred cells after 14 d.p.i. (data not shown), possibly due to the high turnover of cells during infection. Rather, we used mixed bone marrow chimeras to examine a cell-intrinsic or cell-extrinsic requirement for Eomes during ILC1-like cell expansion. In uninfected mixed bone marrow chimeras reconstituted with WT cells and either Eomesf/f or Eomes cKO cells, the contributions of Eomesf/f and Eomes cKO cells to CD49a+ cells were comparable, consistent with CD49a+ cells being Eomes-independent ILC1s (Figure 7D). This degree of chimerism did not change upon infection of WT:Eomesf/f chimeras. However, infection of WT:Eomes cKO chimeras resulted in a significant reduction of CD49a+ cells of Eomes cKO origin. Although there were a few CD49a+ ILC1s of Eomes cKO origin, consistent with Eomes-independent ILC1 origin, T. gondii infection resulted in ILC1-like cells that were mostly dependent on a cell-intrinsic effect of Eomes in NKp46-expressing cells, that is, NK cells. Therefore most T. gondii-induced ILC1-like cells are ex-NK cells.

We postulated that STAT4 may play a role in the expansion of ILC1-like cells because STAT4 and IL-12 signaling is critical for NK cell and ILC1 activation during T. gondii infection (Hunter et al., 1994; Cai et al., 2000; Klose et al., 2014). To test the relevance of this signaling in vivo, we infected WT:Stat4-/- mixed bone marrow chimeras. Indeed, STAT4-deficient ILC1-like cells were diminished following infection, while chimerism of NK cells and ILC1s remained equal between uninfected and infected chimeric mice (Figure 7e), suggesting that T. gondii-induced ILC1-like cells were dependent on STAT4. Additionally, in vitro culture of splenocytes from infected mice resulted in an increased frequency of ILC1-like cells following culture in IL-2 and IL-12, compared to culture in IL-2 alone (Figure 7—figure supplement 1B), suggesting that IL-12 may contribute to ILC1-like cell expansion. However, culture of purified NK cells from infected mice did not result in Eomes downregulation (Figure 7—figure supplement 1C), showing there may be IL-12 cell-extrinsic effects involved in this conversion. Notably, T. gondii-induced ILC1-like cells stably maintained their phenotype after 2 days in culture (Figure 7—figure supplement 1C). Taken together, these results suggest that STAT4 and IL-12 contribute to ILC1-like cell expansion in the context of T. gondii infection, with contributions from additional factors as well.

Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes

Our scRNA-seq data suggested that T. gondii infection drastically rewires NK cells and ILC1s to induce permanent changes. To provide confirmatory evidence, we performed bulk RNA sequencing (RNA-seq) to inform epigenomic analyses, even though we realize that these approaches lose single cell resolution. For this analysis, we used splenocytes, sorted into NK cells (Ly6C CD49a) from uninfected and infected mice, and ILC1-like cells (Ly6C+ CD49a+) from infected mice, which were accurately identified Eomes+ and Eomes cells, respectively (Figure 8—figure supplement 1A). With respect to our scRNA-seq analysis, these cells represent Eomes+ (conventional) NK cells from uninfected and infected mice, and T. gondii-induced ILC1-like cells (both converted NK cells and Ly6C+ ILC1s), of which most were converted NK cells (Figures 6 and 7B). Principal component analysis and hierarchical clustering showed a higher degree of similarity between NK cells from uninfected and infected mice, relative to ILC1-like cells (Figure 8A,B). As expected, Ly6c1, Ly6c2, Itga1, and Eomes were differentially expressed (Figure 8C). We found extensive differences between NK cells and ILC1-like cells, including differences in the expression of surface markers, transcription factors, secreted factors, adhesion molecules, chemokine receptors, and signaling molecules (Figure 8D).

Figure 8 with 1 supplement see all
Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes.

(A) Principal component analysis using top 2000 most variable genes from RNA-seq analysis comparing NK cells from spleens of uninfected and infected mice and Ly6C+ ILC1s (ILC1-like cells) from d35-infected mice, each dot represents a sample from different mice, n = 3 mice (NK cells-uninfected) or n = 5 mice (NK cells-infected and Ly6C+ ILC1-like). Color legend shown applies to all panels. (B) Unsupervised hierarchical clustering of each sample in (A). (C) Volcano plots showing Log2(Fold Change) differences versus –Log10(False Discovery Rate) for indicated comparisons, using pooled data from each indicated sample type. Genes exhibiting Log2FC > 1 and FDR < 0.1 are colored. (D) Heatmaps showing centered DESeq2 variance-stabilized expression values of select genes exhibiting Log2FC > 1 and FDR < 0.1, n = 3 mice (NK cells-uninfected) or n = 5 mice (NK cells-infected and Ly6C+ ILC1-like). Each column represents a different mouse sample of a given cell type, indicated by color code shown in (A). (E) Principal component analysis from ATAC-seq analysis comparing NK cells from spleens of uninfected and infected mice and Ly6C+ ILC1s (ILC1-like cells) from d35-infected mice, n = 3 mice. (F) Unsupervised hierarchical clustering of samples in (E). (G) Representative UCSC genome browser tracks showing ATAC-seq peaks in NK cells from uninfected mice, and NK cells and Ly6C+ ILC1s from d35-infected mice, at the Eomes locus. Differentially accessible REs are highlighted in blue.

https://doi.org/10.7554/eLife.47605.015

Since NK cells and ILC1s display distinct patterns of chromatin accessibility (Shih et al., 2016), and infection can induce long-lasting epigenomic changes in NK cells (Lau et al., 2018), we performed the assay for accessibility for transposase-accessible chromatin using sequencing (ATAC-seq) (Buenrostro et al., 2015) to compare the NK cells and ILC1-like cells present in T. gondii-infected mice at the epigenomic level. We found widespread chromatin remodeling in ILC1-like cells, which clustered separately from NK cells (Figure 8E,F). Most differentially accessible regions fell within intronic and intergenic regions, consistent with categorization as putative enhancers (Figure 8—figure supplement 1B).

We organized differentially accessible regulatory elements (REs) into a non-redundant peak set containing six groups (Figure 8—figure supplement 1C,D). Groups 1, 3, and 5 contained REs that were uniquely more accessible in uninfected NK cells, NK cells from infected mice, and ILC1-like cells, respectively. Groups 2, 4, and 6 contained REs that were shared between two groups. Group 2 encompassed REs that were more accessible in both NK cell groups relative to ILC1-like cells, and accounted for the largest fraction of peaks, showing that NK cells from both uninfected and infected mice share many epigenetic features. Group 4, which contained REs that were more accessible in both NK cells and ILC1-like cells from infected mice relative to uninfected NK cells, was the second largest group, suggesting that infection may induce epigenetic changes common to both populations.

We directly compared the REs in groups 3 and 5 to identify additional differences between NK cells and ILC1-like cells following infection. Analysis of transcription factor binding motifs revealed motifs that were significantly enriched in each population, such as NF-κb in group 3, whose motif was present in 13.2% of REs, and Klf4 in group 5, whose motif was present in 25.8% of REs (Figure 8—figure supplement 1E). We also identified the specific loci that contained the most differentially accessible REs, and noted that the presence of more accessible REs generally correlated with greater gene expression. Notably, many of the epigenetic features shared by memory NK cells and memory CD8+ T cells (Lau et al., 2018) were among the loci that gained accessibility in ILC1-like cells (Figure 8—figure supplement 1F). Among the differentially accessible regions were the Eomes and Tbx21 loci, supporting our data above detailing expression changes of these transcription factors (Figure 8G, Figure 8—figure supplement 1G). Overall, our data suggest that T. gondii induces the conversion of NK cells into ILC1-like cells in a process that encompasses changes in gene expression and chromatin accessibility.

Discussion

Infection with T. gondii, a natural mouse pathogen, causes the expansion of a novel ILC1-like subpopulation that stably persists even after acute infection resolves. These ILC1-like cells are heterogeneous, due to contributions from both ILC1s and NK cells, though NK cells give rise to most ILC1-like cells by means of Eomes downregulation. These findings disrupt current notions surrounding NK cells and ILC1s, which were recently established as discrete ILC lineages (Vivier et al., 2018), and exemplify the limitations of categorizing NK cells and ILC1s based solely on their phenotypes under steady-state conditions.

Previous studies indicated that Eomes downregulation may occur in NK cells within the tumor microenvironment (Gill et al., 2012; Gao et al., 2017) and in vitro (Cortez et al., 2016). Akin to the intermediate ILC1s (intILC1s) described within tumors (Gao et al., 2017), we found T. gondii infection induced Eomes+ CD49a+ NK cells in the liver, which are possibly intermediates between NK cells and ex-NK cells. However, our findings differ in several significant ways. The tumor studies indicated that Eomes NK cells were restricted to tumors and emphasized the importance of the microenvironment (Gao et al., 2017; Gill et al., 2012), concluding that within tumors, Eomes downregulation transiently silences NK cells to hamper immunosurveillance (Silver and Humbles, 2017). There was no evidence presented that these Eomes cells can circulate, though they proliferate when adoptively transferred into lymphocyte-deficient hosts. Moreover, it is not clear if these cells persist in the absence of tumor. By contrast, T. gondii-induced ILC1-like cells are disseminated throughout the circulation, retain the ability to produce IFNγ, do not produce TNFα, and are maintained in the absence of ongoing stimulus.

Our findings further indicate a permanent transformation of T. gondii-induced ILC1-like cells rather than a transient response to inflammation, a notion that is further bolstered by the observations that ILC1-like cells possess a unique gene expression profile. Moreover, T. gondii infection induced epigenetic modifications in NK cells and ILC1-like cells, although our analysis did not specifically examine each of the different individual NK and ILC1-like subsets we identified by scRNA-seq. However, these modifications were extensive and could not be readily explained by heterogeneity in the ILC1-like cells that we discovered by scRNA-seq. Nonetheless, our studies go beyond just the differences between tumor-induced and T. gondii-induced Eomes downregulation. Our findings indicate that DX5 and CD49a expression to identify NK cells and ILC1s may not always faithfully reflect Eomes expression, as is the case during early T. gondii infection. Moreover, although there is clear evidence supporting conversion from NK cells to Eomes NK cells, such as intILC1s (Gao et al., 2017), there is a general inability to distinguish between preexisting ILC1s and de novo converted ILC1s. Indeed, this may explain discrepancies that currently exist within the field, such as the conflicting report that ILC1-like cells confer protection against certain tumors (Dadi et al., 2016). Thus, our studies suggest that ILC1s may be more heterogeneous than currently thought, as they can arise from distinct precursors (Vivier et al., 2018).

In T. gondii infection, IL-12 is critical for NK cell activation (Gazzinelli et al., 1993) and our data suggest that it can have long-lasting effects. This parallels the requirements for development of memory and memory-like NK cells induced by MCMV and cytokine stimulation (Cooper et al., 2009; Sun et al., 2012; Romee et al., 2012). In addition to IL-12 dependence, MCMV-induced memory NK cells and T. gondii-induced ILC1-like cells share Ly6C expression, as well as alterations in their receptor repertoire, although ILC1-like cells primarily express the inhibitory receptor NKG2A while MCMV-induced memory NK cells are Ly49H+. Moreover, memory and memory-like NK cells have few markers that differentiate them from resting NK cells, whereas NK cells converted by T. gondii infection lose expression of Eomes and gain expression of Ly6C, KLRG1, CX3CR1, and Nrp-1, with scRNA-seq revealing global transcriptional differences that identify them as a discrete subpopulation.

The persistence of ILC1-like cells after clearance of infection is reminiscent of classical immune memory and suggests that ex-NK cells play a role beyond what has been attributed to NK cells and ILC1s in T. gondii infection thus far. One possibility is that ILC1-like cells are an inflammatory subpopulation, such as the inflammatory ILC2s that gain circulatory capacity in response to activation by cytokines or infection (Huang et al., 2018). These inflammatory ILC2s can be distinguished from tissue-resident ILC2s based on their increased expression of KLRG1 and S1P receptors, features that are also characteristic of T. gondii-induced ILC1-like cells, but not steady-state tissue-resident NK cells. Most ILC1-like cells express CX3CR1, which has previously been shown to regulate NK cell recruitment into the circulation (Ponzetta et al., 2013; Sciume et al., 2011). Another possibility is that ILC1-like cells may provide a protective role in subsequent T. gondii infections, as shown previously (Denkers et al., 1993), although this finding remains controversial (Goldszmid et al., 2007). Moreover, we have not been able to show that repeated injection of an avirulent T. gondii strain confers NK1.1-dependent protection against subsequent lethal re-challenge. Regardless, we have observed ILC1-like cell expansion following repeated exposure to avirulent T. gondii strains, and future studies may illuminate how gaining circulatory capacity affects the functionality of ILC1-like cells, and how these cells may contribute to subsequent immune responses to T. gondii.

In summary, we found that T. gondii infection induced permanent changes to NK cells and ILC1s, including conversion of NK cells into ILC1-like cells. Our studies indicate that the current system of ILC classification, based on their phenotype and development under steady state conditions, may not apply following inflammation. Rather, plasticity may give rise to populations that resemble one another at first glance, but actually represent the convergence of multiple developmental paths to form interrelated populations.

Materials and methods

Key resources table
Reagent type (species)
or resource
DesignationSource or
reference
IdentifiersAdditional
information
Chemical compound, drugD-Luciferin, Potassium SaltGold BiotechnologyCat#LUCK-1G; CAS 115144-35-9
Chemical compound, drugSulfadiazineSigmaCat#S8626-25G
Chemical compound, drugUracilSigmaCat#U1128
Chemical compound, drugPercollSigmaCat#P1644
Chemical compound, drugRecombinant murine IL-12Pepro TechCat#210–12
Chemical compound, drugRecombinant mouse IL-18MBLCat#B002-5
Chemical compound, drugRecombinant murine IL-15Peptro TechCat#210–15
Chemical compound, drugDNase ISigmaCat#10104159001
Chemical compound, drugCollagenase Type IVSigmaCat#C5138-100mg
Commercial assay or kitFoxp3/Transcription Factor Staining Buffer SeteBioscienceCat#00-5523-00
Commercial assay or kitEasySep MagnetBD BiosciencesCat#1800
Commercial assay or kitEasySep Mouse Streptavidin Rapidspheres Isolation KitBD BiosciencesCat#19860
Commercial assay or kitNextera Index KitIlluminaCat#FC-121–1011
Commercial assay or kitSMARTer PCR cDNA Synthesis KitClontechCat#634926
Genetic reagent (Homo sapiens)Human: HFFJohn C. Boothroyd
Cell line (Rattus norvegicus, Mus musculus)2.4G2 hybridomaATCCATCC HB-197
Cell line (Rattus norvegicus, Mus musculus)PK136 hybridomaATCCATCC HB-191
Genetic reagent (Mus musculus)wild-type; C57BL/6NCrCharles RiverCat#556
Genetic reagent (Mus musculus)CD45.1+;B6.SJL-PtprcaPepcb/BoyCrCrlCharles RiverCat#564
Genetic reagent (Mus musculus)Balb/c; BALB/cAnNCrCharles RiverCat#555
Genetic reagent (Mus musculus)NKp46iCre; Ncr1tm1.1(icre)Viv/JEric VivierMGI:5308410
Genetic reagent (Mus musculus)Eomesf/f; B6.129S1(Cg)-Eomestm1.1Bflu/JThe Jackson LaboratoryMGI:4830338, Cat#017293
Genetic reagent (Mus musculus)Stat4-/-; C.129S2-Stat4tm1Gru/JThe Jackson LaboratoryMGI: 1857248, Cat#002826
Genetic reagent (Mus musculus)Tbx21-/-; B129.S6-Tbx21tm1Glm/JThe Jackson LaboratoryMGI: 2180194, Cat#004648
Genetic reagent (Mus musculus)Tgfbr2f/f; B6;129-Tgfbr22tm1Karl/JThe Jackson LaboratoryCat#012603, MGI: 98729
Genetic reagent (Mus musculus)Zeb2-GFP; Zfhxlbtm2.1YhiKenneth Murphy
Genetic reagent (Toxoplasma gondii)Prugniaud; Pru; PRU-FLuc-GFPJohn C. Boothroyd
Genetic reagent (Toxoplasma gondii)WT T. gondii; Pru∆ku80 ∆hxL. David Sibley
Genetic reagent (Toxoplasma gondii)Δgra4 T. gondii; Pru∆ku80 ∆hx ∆gra4::HX/mcherryL David Sibley
Software, algorithmFlowjo 10Treestarhttps://www.flowjo.com/ ; RRID: SCR_008520
Software, algorithmPrism 7Graphpadhttps://www.graphpad.com/ ; RRID: SCR_002798
Software, algorithmBowtie2 version 2.4.3.2bLangmead and Salzberg, 2012http://bowtie-bio.sourceforge.net/bowtie2/manual.shtml
Software, algorithmSamtools version 1.4Li et al., 2009http://samtools.sourceforge.net/
Software, algorithmPicard Tools version 2.18.14Broad Institutehttp://broadinstitute.github.io/picard/
Software, algorithmBEDTools version 2.27.0Quinlan and Hall, 2010https://bedtools.readthedocs.io/en/latest/
Software, algorithmMACS2 version 2.1.0Zhang et al., 2008https://github.com/taoliu/MACS
Software, algorithmdeepTools version 3.1.2Ramírez et al., 2014https://deeptools.readthedocs.io/en/develop/
Software, algorithmHomer version 4.10Heinz et al., 2010http://homer.ucsd.edu/homer/
Software, algorithmRStudio version 3.5.1R Core Team 2014https://www.r-project.org/
Software, algorithmBioconductor package DESeq2 version 1.21.22Love et al., 2014http://bioconductor.org/packages/release/bioc/html/DESeq2.html
Software, algorithmKallisto version 0.44.0Bray et al., 2016https://pachterlab.github.io/kallisto/download
Software, algorithmGSEAMootha et al., 2003; Subramanian et al., 2005http://software.broadinstitute.org/gsea/index.jsp
Software, algorithmSeuratButler et al., 2018https://cran.r-project.org/web/packages/Seurat/index.html

Mice

Eomesf/f, Tbx21-/-, and Stat4-/- were purchased from The Jackson Laboratory. C57BL/6, CD45.1+, and BALB/c mice were purchased from Charles River. Ncr1iCre mice were a kind gift from Eric Vivier. Zeb2-GFP mice were a generous gift from Kenneth Murphy (Wu et al., 2016). Eomes-GFP mice were graciously provided by Thierry Walzer (Daussy et al., 2014). Ncr1iCre were bred to Eomesf/f mice to generate Eomes cKO mice and Cre-negative littermate controls. Rag2-/- were bred to Il2rg-/- to generate Rag2-/-Il2 rg-/- mice. Age and sex-matched animals were used in all experiments. Mice were infected at 6–12 wk of age. All protocols were approved by the Institutional Animal Care and Uses Committee (Washington University School of Medicine, St. Louis, MO) under animal protocol number 20160002.

Parasites

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PRU-FLuc-GFP Type II strain of T. gondii was a generous gift from John C. Boothroyd and used in all infections unless otherwise specified. Pru∆ku80∆hx∆gra4::HX/mCherry and the wildtype parental strain Pru∆ku80∆hx were previously described (Jones et al., 2017). The attenuated Cps1-1 mutant on the type I RH background was described previously (Fox and Bzik, 2002).

All T. gondii strains used in this study were maintained in human foreskin fibroblast (HFF) monolayers grown in D-10 medium (Dulbecco’s modified Eagle medium, 10% fetal bovine serum (FBS), 2 mM glutamine, 10 mM HEPES pH 7.5, 20 μg/mL gentamicin), maintained at 37°C with 5% CO2. The Cps1-1 mutant was grown as described above but supplemented with 200 μM uracil (Sigma). Mature parasites were lysed from host cells by vigorous pipetting and egressed parasites were filtered through 3 μm polycarbonate membranes and resuspended in HHE medium (Hanks’ balanced salt solution, 10 mM HEPES, 0.1 mM EGTA). Cell cultures were determined to be mycoplasma-negative using the e-Myco plus kit (Intron Biotechnology).

Infection

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Mice were injected intraperitoneally (i.p.) with 200 PRU-FLuc-GFP, Pru∆ku80∆hx, or Pru∆ku80∆hx∆gra4::HX/mCherry tachyzoites that were propagated in culture as described above. In indicated experiments, mice were treated with 0.5 g/L sulfadiazine in drinking water to suppress parasite growth. To generate non-persistent infections, 1 × 105 Cps1-1 tachyzoites were injected three times, 2 weeks apart.

Luciferase imaging

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Mice were injected i.p. with 150 mg D-luciferin (Gold Biotechnology) per kg body weight, incubated for 10 min, then anesthetized with continuous isoflurane anesthesia at a flow rate of 1 L/min. Images were captured using an IVIS Spectrum In Vivo Imaging System (Perkin Elmer). Luminescence was quantitated using Living Image software (Perkin Elmer). NK1.1-depleted mice and control mice were injected i.p. with 100 μg of anti-NK1.1 or isotype control antibody 3 days and 1 day prior to infection. Purified anti-NK1.1 antibody and isotype control were generated at the Rheumatic Diseases Core Center Protein Purification and Production Facility using the PK136 hybridoma (ATCC) and MAR 18.5 hybridoma (ATCC), respectively.

Cell isolation

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Spleens were mashed through a 70 μm cell strainer and treated with Tris-NH4Cl to lyse red blood cells. Livers were mashed through a 70 μm cell strainer, resuspended in isotonic 38.5% Percoll (Sigma- Aldrich), centrifugated at 325 x g for 20 min, and treated with Tris-NH4Cl. Peritoneal cells were isolated by lavage of the peritoneal cavity with PBS. Bone marrow was flushed from femurs and tibias, mashed through a 70 μm cell strainer, and treated with Tris-NH4Cl. Lymph nodes were mashed through a 70 μm cell strainer. Brains were mashed through a 70 μm cell strainer, resuspended in 38.5% isotonic Percoll, and centrifugated at 325 x g for 20 min. Lungs were perfused with PBS, minced, digested in RPMI-1640 containing 2% FBS, 1 mg/mL Collagenase Type IV (Sigma-Aldrich), and 0.2 mg/mL DNase (Sigma-Aldrich), mashed through a 70 μm cell strainer, resuspended in 38.5% isotonic Percoll, and centrifugated at 325 x g for 20 min. Uterus and salivary gland were minced, digested in RPMI-1640 containing 0.17 mg/mL Liberase TL (Sigma-Aldrich) and 0.1 mg/mL DNase (Roche), mashed through a 70 μm cell strainer, resuspended in 38.5% isotonic Percoll, and centrifugated at 325 x g for 20 min.

Flow cytometry and cell sorting

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Cells were stained with Fixable Viability Dye and Fc receptors were blocked with 2.4G2 hybridoma (ATCC) culture supernatants prior to staining in PBS containing 2% FBS and 2.5 mM EDTA on ice. Data was acquired using a FACSCanto instrument (BD Biosciences) or FACSAria instrument (BD Biosciences) using FACSDiva software (BD Biosciences). Data was analyzed with Flowjo v10 (Treestar).

For cell sorting, splenocytes were enriched for NK1.1+ NKp46+ cells by negative selection. Splenocytes were incubated with 0.2 μg/mL biotin mouse CD4, 0.2 μg/mL biotin anti-mouse CD8, and 1 μg/mL biotin anti-mouse CD19. One hundred μL of EasySep Mouse Streptavidin Rapidspheres (BD Biosciences) were added per 1 × 108 splenocytes. Cells were placed in an EasySep magnet (BD Biosciences) and enriched cells were poured off and subjected to extracellular staining. Sorting was performed using a FACSAria instrument (BD Biosciences) using FACSDiva software (BD Biosciences). NK cells were identified as CD3 CD19 NK1.1+ NKp46+ Eomes-GFP+ CD49a and T. gondii-induced ILC1-like cells were identified as CD3 CD19 NK1.1+ NKp46+ Eomes-GFP CD49a+.

Stimulations and intracellular staining

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Following extracellular staining, cells were fixed with FoxP3/Transcription Factor Staining Buffer Set for 30 min at room temperature and washed with 1x Permeabilization buffer (eBiosciences). Transcription factor antibodies were diluted in 1x FoxP3 permeabilization buffer and cells were incubated for 30 min at room temperature.

To assess Eomes downregulation after culture in IL-12, 5 × 106 splenocytes were cultured in R-10 medium (RPMI-1640 medium containing 10% FBS, 2 mM glutamine, 100 U/mL penicillin, and 100 μg/mL streptomycin) with 300 IU/mL IL-2 with 20 ng/mL IL-12 (Pepro Tech). Unstimulated control wells contained only 300 IU/mL IL-2.

For detection of IFNγ production, 5 × 106 splenocytes were cultured for 5 hr in R-10, with the addition of 20 ng/mL IL-12, 20 ng/mL IL-12 + 5 ng/mL IL-18, or 0.5 μg/mL PMA + 4 μg/mL Ionomycin. Brefeldin A was added after 1 hr.

Generation of bone marrow chimeras

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Donor bone marrow was harvested by flushing femurs and tibias and mashing through a 70 μm cell strainer. Cells were mixed in a 1:1 ratio with CD45.1+ bone marrow, and intravenously injected into irradiated mice. Recipient mice were lethally irradiated (900 rad) and reconstituted with a 1:1 ratio of CD45.1+ bone marrow cells and CD45.2+ Eomes cKO, Eomesf/f, Tbx21-/-, or Stat4-/- bone marrow cells (Kaplan et al., 1996; Zhu et al., 2010; Finotto et al., 2002). Mice were maintained on sulfamethoxazole/trimethoprim oral suspension added to the drinking water for 2 weeks after reconstitution and used for experiments 6–8 weeks after reconstitution. To prevent chimeric mice from succumbing to acute T. gondii infection, bone marrow chimeras were treated with 0.5 g/L sulfadiazine in drinking water beginning 10 d.p.i. and maintained on sulfadiazine until the end of the experiment.

Single-cell RNA-Seq

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Sorted cells were subjected to droplet-based 3’ end massively parallel single-cell RNA sequencing using Chromium Single Cell 3’ Reagent Kits as per manufacturer’s instructions (10x Genomics). The libraries were sequenced using a HiSeq3000 instrument (Illumina).

Sample demultiplexing, barcode processing, and single-cell 3’ counting was performed using the Cell Ranger Single-Cell Software Suite (10x Genomics). Cellranger count was used to align samples to the mm10 reference genome, quantify reads, and filter reads with a quality score below 30.

The Seurat package in R was used for subsequent analysis (Butler et al., 2018). Genes expressed in fewer than 3 cells and cells that expressed less than 400 or greater than 3500 genes were removed for downstream analysis. Data was normalized using a scaling factor of 10,000 s and nUMI was regressed with a negative binomial model. Principal component analysis was performed using the top 3000 most variable genes and t-SNE analysis was performed with the top 40 PCAs. Clustering was performed using a resolution of 0.8. For heatmaps, the mean expression by all cells within the cluster was used.

RNA sequencing

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RNA was isolated from 5 × 104 sorted cells using Trizol. Libraries were prepared using the Clontech SMARTer Kit. Sequencing was performed using 1 × 50 single-end reads with a HiSeq3000 instrument (Illumina). Reads were quantified using kallisto and differential expression was assessed using the DESeq2 package in R (Bray et al., 2016; Love et al., 2014). Using a log2FC cutoff of 1 and an FDR threshold of 0.1, we identified 657 differentially expressed (DE) genes between the NK cells from uninfected and d35-infected mice, 2288 DE genes between NK cells from infected mice and T. gondii-induced ILC1-like cells, and 1685 DE genes between NK cells from uninfected mice and T. gondii-induced ILC1-like cells. Variance-stabilized transform values were used for subsequent analysis. All plots were generated in R using the ggplot2, pheatmap, and hclust packages. GSEA was performed using the GSEA Preranked module in GenePattern (Subramanian et al., 2005; Mootha et al., 2003; Reich et al., 2006).

ATAC-seq

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Samples were prepared as previously described (Buenrostro et al., 2015), then purified with MinElute spin columns (Qiagen). DNA fragments were amplified using Nextera index adapters as per manufacturer’s instructions (Illumina). Libraries were purified with AMPure XP beads (Beckman Coulter). Three libraries were pooled and sequenced with 2 × 50 paired end reads using a HiSeq3000 instrument (Illumina).

Sequences were aligned to the mm10 reference genome using Bowtie2 (Langmead and Salzberg, 2012). Reads with a quality score below 30 were removed with Samtools (Li et al., 2009) and duplicate reads were filtered with PicardTools (Broad Institute). Peaks were called using MACS2 (Zhang et al., 2008) with an FDR cutoff of 0.05. Narrowpeak files generated from MACS2 were converted to Bigwig files with deepTools (Ramírez et al., 2014), and visualized using the UCSC genome browser. Differential peaks were identified using Homer (Heinz et al., 2010) with a Log2FC > 1 and an FDR cutoff of 0.05. Heatmaps of differentially accessible regions were generated with deepTools. Transcription factor binding motifs were identified de novo with Homer.

Across all samples, we identified 71,504 peaks. We further analyzed 9640 discrete peaks that displayed two-fold changes between at least two groups. Between NK cells from control and infected mice, there were 1809 differential peaks (1445 were larger in the NK cells from infected mice and 364 were larger in NK cells from uninfected mice), between NK cells from infected mice and T. gondii-induced ILC1-like cells, there were 6710 differential peaks (4572 were larger in the NK cells and 2138 were larger in T. gondii-induced ILC1-like cells), and between NK cells from uninfected mice and T. gondii-induced ILC1-like cells, there were 5938 differential peaks (3065 were larger in the uninfected NK cells and 2973 were larger in T. gondii-induced ILC1-like cells).

Statistical analysis

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Prism (GraphPad) was used for statistical analysis. Student’s t-test was used for comparison of two groups and two-way ANOVA with Bonferroni correction was used in analyses involving multiple comparisons. p-Values are shown in figures and figure legends. In all graphs, points represent biological replicates, bar position represents the mean, and error bars represent + s.e.m.

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Decision letter

  1. Alan Sher
    Reviewing Editor; NIH, NIAID, United States
  2. Tadatsugu Taniguchi
    Senior Editor; Institute of Industrial Science, The University of Tokyo, Japan
  3. Chris Hunter
    Reviewer; The University of Pennsylvania
  4. Jinfang Zhu
    Reviewer; National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States
  5. Eric O Long
    Reviewer; National Institute of Allergy and Infectious Diseases, United States

In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.

Thank you for submitting your article "Toxoplasma gondii infection drives conversion of NK Cells into ILC1s" for consideration by eLife. Your article has been reviewed by Tadatsugu Taniguchi as the Senior Editor, a Reviewing Editor, and three reviewers. The following individuals involved in review of your submission have agreed to reveal their identity: Chris Hunter (Reviewer #1); Jinfang Zhu (Reviewer #2); Eric O Long (Reviewer #3).

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

Summary:

Natural Killer (NK) and the ILC1 subset of innate lymphoid cells share related functions in host defense but have been argued to arise from distinct pathways. Park et al. present new evidence challenging this concept. They show that murine Toxoplasma gondii infection promotes the differentiation of NK cells into an ILC1-like cell population which is stable and long-lasting, even after the infection has been cleared. These T.gondii induced cells, unlike Eomes+CD49a- NK cells, are Eomes-CD49a+T-bet+ and therefore resemble ILC1 cells. The authors additionally show that their differentiation involves Eomes down regulation and is STAT-4 dependent, However, in common with NK cells and distinct from ILC1 the T. gondii induced "ILC-like" population circulates to blood and lungs. Finally, the authors employ single cell RNA-seq to examine the heterogeneity of the major T. gondii induced innate lymphocyte populations and their NK vs ILC relatedness as assessed by gene expression. Together, their observations establish a previously unappreciated developmental link between NK and ILC1 cells in the context of infection.

The three reviewers and editor agree that this is an important contribution that sheds new light on the developmental relationship of NK and ILC1 cells, a scientific issue that has received considerable attention in the innate immunity field. Although extensive, most of the criticisms raised can be addressed by revisions to the manuscript. One additional experiment is requested to provide a missing control.

Essential revisions:

All reviewers had a major concern about how this new population of T. gondii induced innate cells should be referred to in the manuscript. Based on the single cell RNA-seq data, these cells (cluster 10) are still closer to NK cells than to ILC1s (Figure 5F and Figure 6—figure supplement 1E) despite their loss in Eomes expression and acquisition of CD49a expression. Thus, one could easily think of them as "Eomes negative NK" or "ex-NK" cells rather than ILC1s, and to simply refer to them as Eomes-CD49a+ ILC1 cells may be misleading. For this reason, the authors should modify the title of the paper and change their designation throughout the manuscript. We suggest "ILC1-like" as a good descriptor. In addition, although it is clear that the "Eomes negative NK" cells that are generated during T. gondii infection are transcriptionally and epigenetically distinct from the NK cells in the steady state and NK cells after infection (Figure 7 and Figure 8—figure supplement 1), these "Eomes negative NK" cells referred to as "T. gondii-induced ILC1s" were not directly compared with classical ILC1s. Based on the single cell RNA-seq data, these cells may not express many of the ILC1-related signature genes. Therefore, again, the authors need to be cautious in referring to them as ILC1 cells.

A second concern was that the NK 1.1 depletion shown in Figure 1—figure supplement 1 was performed with a PBS rather than isotope matched immunoglobulin control which is considered unacceptable. The authors should repeat at least once with proper control Ig to make sure this is not issue. It is not necessary to repeat entire survival curve just experiments shown in A and B and initial survival to make sure there is no death in controls vs. antibody treated.

1) Figure 3E-H is focused on the liver, where populations of memory and tissue-resident NK cells reside. Do the authors have data sets for the liver in Figure 3A-C? Do they express Ly6C? Including them in the bar graph of Figure 3C would be useful to identify if the liver trends with the lungs or with the brain (both sites of parasite infection/replication)…or alternatively authors should continue to focus on the lung throughout the entirety of Figure 3.

2) The conclusion of Figure 3F is that "Eomes expression generally remained the same". However, for the representative flow plot of liver NK cells, the authors chose the lowest% of Eomes negative, while in the bar graph the rest of the points show that 20-50% of Eomes+ NK cells became Eomes-ve after transfer and migration to the liver. Please reword statement appropriately as Eomes expression is really not the same when the data are pooled.

3) The interesting point of Figure 3G is the upregulation of CD49a on Eomes+ NK cells post-infection. However, this population is eliminated from the subsequent histograms showing Ly6C expression. It may be of interest to note whether Ly6C expression by Eomes+CD49a+ cells is more similar to ILC1s or NK cells, or occurs at an intermediate level (which would make sense if that population is being seeded from both NK cells and ILC1s).

4) There are a lot of data represented in Figure 4C-D, without much rationale or interpretation provided in the text suggesting that items may be more appropriate for a supplemental figure.

5) The CD45.2/.1 appears to be switched on Figure 6—figure supplement 1A.

6) Although the contour plots don't show outliers, the bottom panel of Figure 3E says 3.66%, but there's nothing in the gate, which is a bit misleading.

7) The% of Eomes cKO during infection is missing in Figure 6D (bottom).

8) The marker Ly6C figures prominently in most of the paper. What is the significance of its expression and of its induction by T. gondii infection? Please provide background.

9) A recurrent problem is insufficient description of Figures. In several cases (e.g. Figure 4, Figure 5A), the source of cells used for analysis is not given in the Figure, the legend or the text. It would help to include the source of cells, eg liver or spleen, in each of these places.

10) As suggested above it would strengthen the manuscript if the authors should characterize the Eomes+CD49a+ cells found in the liver after T. gondii infection in a greater detail. Do they also express Ly6C?

11) In Figure 3F, ~30% of "ILC1s" re-express Eomes upon transfer; this should be discussed.

12) Figure 3D, the cell labels appear to be switched. Please check.

13) IL-7Ris an important marker to distinguish NK cells from ILC1s but the cells in cluster 10 do not express IL-7R as shown in Figure 5F. How about IL-2Rb? If possible the dependence of these NK/ILC1 subsets on IL-7 and/or IL-15 should be either tested or discussed.

14) Figure 3G is confusing. While there are 3 subsets for the combination of CD49a and Eomes expression (upper flow plots) only 2 are shown on the lower panels for Ly6C expression. What are they? Are the colors supposed to match between the top and low panels? Even so, it is not clearly visible.

15) Subsection “Expansion of ILC1s among circulating cells”. "Ly6C was expressed by a higher percentage." Percentage of what?

16) A number of different markers were used to distinguish among cell subsets, as for example in Figure 4. In many cases, no reason is given for the choice of markers. On what basis were they selected? Besides a phenotypic distinction of subsets, do they contribute to an understanding of the function of these different cells? Please clarify in each case.

17) In Figure 4D, lower panels, p values are indicated for different comparisons between markers. The main comparisons should be between uninfected and infected cells, and between NK and ILC1. For what reason are NK cells from uninfected mice compared to ILC from infected mice for every marker measured?

18) Figure 5G, the color gradient, used to presumably show expression level or frequency, does not allow visual discrimination. A different color scale is needed. Some scales go up to 2, others up to 5. What do they indicate?

19) Subsection “NK Cells downregulate Eomes during T. gondii infection”, "the numbers of CD49a+ and CD49a+ Ly6C+ cells were significantly reduced in Eomes cKO compared to Eomes f/f controls (Figure 6A,B)." That result is in 6B. Figure 6A is very different, it shows that the frequency of these cells is higher in Eomes cKO. This difference is not explained. In contrast, the experiment with bone marrow chimeras shown in Figure 6D is very clear. Why are changes in the relative cell frequencies so different from changes in cell numbers?

20) The columns in Figure 7D are not defined. The corresponding legend is dense. It looks like columns may have been grouped as NK-uninf, NK-inf and ILC1. Does each column represent a different mouse?

21) Subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes”. "NK cells share many epigenetic features…" Share with whom?

22) Subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes”. "Somewhat surprisingly" Since T. gondii infection has a large impact on both NK cells and ILC1 cells, why are epigenetic changes common to both populations surprising?

23) Sequencing analysis shows there are two genes for Ly6C. Does the analysis of phenotypes with anti-Ly6C antibody detect both? What is the significance of having two genes?

24) Subsection “T. gondii infection results in ILC1 expansion.”. A symbol that is neither an "a" nor a Greek letter α appears in "a-NK1.1". What is it? The context suggests it is an antibody that causes depletion of NK1.1+ cells in mice. If so, it should be described. What does the symbol represent? The symbol appeared again on subsection “T. gondii-induced ILC1s are distinct from NK Cells and ILC1s” in "TNFa". It should be replaced by the Greek letter α.

25) Visually, Figure 8—figure supplement 1C does not convey a clear message. How were the subsets defined? What could be their biological relevance?

26) The two comparisons made from the ATAC-seq analysis in Figure 7G for Eomes and Figure 8—figure supplement 1F for T-bet show small differences. Is there a way to express a statistical significance? The changes do not look convincing.

27) The legend to Figure 8—figure supplement 1E Figure does not adequately explain the Figure. What does the figure show?

https://doi.org/10.7554/eLife.47605.023

Author response

Essential revisions:

All reviewers had a major concern about how this new population of T. gondii induced innate cells should be referred to in the manuscript. Based on the single cell RNA-seq data, these cells (cluster 10) are still closer to NK cells than to ILC1s (Figure 5F and Figure 6—figure supplement 1E) despite their loss in Eomes expression and acquisition of CD49a expression. Thus, one could easily think of them as "Eomes negative NK" or "ex-NK" cells rather than ILC1s, and to simply refer to them as Eomes-CD49a+ ILC1 cells may be misleading. For this reason, the authors should modify the title of the paper and change their designation throughout the manuscript. We suggest "ILC1-like" as a good descriptor. In addition, although it is clear that the "Eomes negative NK" cells that are generated during T. gondii infection are transcriptionally and epigenetically distinct from the NK cells in the steady state and NK cells after infection (Figure 7 and Figure 8—figure supplement 1), these "Eomes negative NK" cells referred to as "T. gondii-induced ILC1s" were not directly compared with classical ILC1s. Based on the single cell RNA-seq data, these cells may not express many of the ILC1-related signature genes. Therefore, again, the authors need to be cautious in referring to them as ILC1 cells.

We thank the reviewers for this helpful suggestion. We too had trouble with the best descriptor for these cells and agree that the suggested descriptor is a good one. We have changed the title and the text throughout the paper to now refer to the T. gondii-induced cells as “ILC1-like cells,” rather than ILC1s.

A second concern was that the NK 1.1 depletion shown in Figure 1—figure supplement 1 was performed with a PBS rather than isotope matched immunoglobulin control which is considered unacceptable. The authors should repeat at least once with proper control Ig to make sure this is not issue. It is not necessary to repeat entire survival curve just experiments shown in A and B and initial survival to make sure there is no death in controls vs. antibody treated.

We have repeated the experiments shown in Supplementary Figure 1A-B, comparing the effects of NK1.1-depletion with an isotype control antibody (mouse IgG2a isotype control, clone MAR 18.5). (Note that the original description of PK136 as an IgG2b is incorrect. We and others found that it is an IgG2a, and thus is the right control.) The Materials and methods section and figure (Figure 1—figure supplement 1A) have been updated, as well as the description of this experiment (Introduction).

1) Figure 3E-H is focused on the liver, where populations of memory and tissue-resident NK cells reside. Do the authors have data sets for the liver in Figure 3A-C? Do they express Ly6C? Including them in the bar graph of Figure 3C would be useful to identify if the liver trends with the lungs or with the brain (both sites of parasite infection/replication)… or alternatively authors should continue to focus on the lung throughout the entirety of Figure 3.

Original Figure 3 was a large figure with data from different organs that apparently was difficult to follow. For example, the original panels for Figure 3A-C showed markers on cells from lung and blood, and not liver whereas the remaining panels showed other organs. By taking the suggestion of the reviewer, we have thus divided original Figure 3 into two separate figures. New Figure 3 now discusses the lung and blood, while new Figure 3—figure supplement 1 shows other organs. New Figure 4 now focuses on the liver specifically. All other figures have been renumbered to account for this additional figure. Where cited in the rebuttal below, we refer to the new figure numbers, unless otherwise noted.

2) The conclusion of Figure 3F is that "Eomes expression generally remained the same". However, for the representative flow plot of liver NK cells, the authors chose the lowest% of Eomes negative, while in the bar graph the rest of the points show that 20-50% of Eomes+ NK cells became Eomes-ve after transfer and migration to the liver. Please reword statement appropriately as Eomes expression is really not the same when the data are pooled.

We rephrased to instead stress how the Eomes expression is high in most transferred NK cells as compared to the transferred ILC1s which mostly remained Eomes-negative (subsection “Expansion of ILC1-like cells among circulating cells”).

3) The interesting point of Figure 3G is the upregulation of CD49a on Eomes+ NK cells post-infection. However, this population is eliminated from the subsequent histograms showing Ly6C expression. It may be of interest to note whether Ly6C expression by Eomes+CD49a+ cells is more similar to ILC1s or NK cells, or occurs at an intermediate level (which would make sense if that population is being seeded from both NK cells and ILC1s).

We have added Ly6C expression by Eomes+ CD49a+ cells to Figure 4D, as well as a bar graph comparing expression of Ly6C by Eomes+ CD49a, Eomes+ CD49a+, and Eomes CD49a+ cells (Figure 4G). Indeed, Ly6C is expressed at intermediate levels in the Eomes+ CD49a+ population, suggesting that the Eomes+ CD49a+ population may be an intermediate. We have added interpretation of the data to the text and updated the figure legends correspondingly (subsection “Expansion of ILC1-like cells among circulating cells”).

4) There are a lot of data represented in Figure 4C-D, without much rationale or interpretation provided in the text suggesting that items may be more appropriate for a supplemental figure.

We have added additional discussion of the significance of the markers CD27 and CD11b as maturation markers (subsection “ILC1-like cells are distinct from NK cells and ILC1s”) and moved these figures to a supplemental figure (Figure 5—figure supplement 1).

5) The CD45.2/.1 appears to be switched on Figure 6—figure supplement 1A.

This was indeed the case. It has been fixed (Figure 6—figure supplement 1).

6) Although the contour plots don't show outliers, the bottom panel of Figure 3E says 3.66%, but there's nothing in the gate, which is a bit misleading.

There are actually points visible within the gate (Figure 4B).

7) The% of Eomes cKO during infection is missing in Figure 6D (bottom).

The percentage has been added to the figure (Figure 7D – 10.3%).

8) The marker Ly6C figures prominently in most of the paper. What is the significance of its expression and of its induction by T. gondii infection? Please provide background.

Previously characterized instances of Ly6C expression by NK cells has been added to the text as well as mention that Ly6C is not expressed by ILC1s in steady-state, at the first mention of Ly6C in the Results section.

9) A recurrent problem is insufficient description of Figures. In several cases (e.g. Figure 4, Figure 5A), the source of cells used for analysis is not given in the Figure, the legend or the text. It would help to include the source of cells, e.g liver or spleen, in each of these places.

The source of cells has been added to the legend and text (Results section and figure legends).

10) As suggested above it would strengthen the manuscript if the authors should characterize the Eomes+CD49a+ cells found in the liver after T. gondii infection in a greater detail. Do they also express Ly6C?

See response to comment 3 above.

11) In Figure 3F, ~30% of "ILC1s" re-express Eomes upon transfer; this should be discussed.

We have added discussion of this observation to the text (subsection “Expansion of ILC1-like cells among circulating cells”).

12) Figure 3D, the cell labels appear to be switched. Please check.

The cell labels were indeed switched and are now correct (Figure 4A).

13) IL-7Ris an important marker to distinguish NK cells from ILC1s but the cells in cluster 10 do not express IL-7R as shown in Figure 5F. How about IL-2Rb? If possible the dependence of these NK/ILC1 subsets on IL-7 and/or IL-15 should be either tested or discussed.

We have added discussion of the Il7r expression pattern to the text (subsection “T. gondii infection induces heterogeneity of NK cells and ILC1s”). Il2rb was highly expressed by all clusters (for reviewers’ reference see Author response image 1) and did not distinguish between clusters and thus was not discussed (same expression level was also seen by flow cytometry of CD122).

Author response image 1

14) Figure 3G is confusing. While there are 3 subsets for the combination of CD49a and Eomes expression (upper flow plots) only 2 are shown on the lower panels for Ly6C expression. What are they? Are the colors supposed to match between the top and low panels? Even so, it is not clearly visible.

The 3 subsets refer to Eomes+ CD49a cells, Eomes+ CD49a+ cells, and Eomes CD49a+ cells. The original figure showed Ly6C expression by Eomes+ CD49a and Eomes CD49a+ cells only, but has been revised to show Ly6C expression of Eomes+ CD49a+ cells, in response to comments 3 and 10 above (Figure 4D).

15) Subsection “Expansion of ILC1s among circulating cells”. "Ly6C was expressed by a higher percentage." Percentage of what?

We intended to compare Ly6C expression by ILC1-like cells in the spleen versus the liver. This is now clarified in the text (subsection “Expansion of ILC1-like cells among circulating cells”).

16) A number of different markers were used to distinguish among cell subsets, as for example in Figure 4. In many cases, no reason is given for the choice of markers. On what basis were they selected? Besides a phenotypic distinction of subsets, do they contribute to an understanding of the function of these different cells? Please clarify in each case.

Discussion of the significance of the markers KLRG1, DNAM-1, CD11b, and CD27 were added (subsection “ILC1-like cells are distinct from NK cells and ILC1s”).

17) In Figure 4D, lower panels, p values are indicated for different comparisons between markers. The main comparisons should be between uninfected and infected cells, and between NK and ILC1. For what reason are NK cells from uninfected mice compared to ILC from infected mice for every marker measured?

Indeed, we primarily intended to compare the ILC1-like cells from infected mice with the NK cells in infected mice, and the ILC1s in uninfected mice. This has now been corrected (Figure 5, Figure 5—figure supplement 1).

18) Figure 5G, the color gradient, used to presumably show expression level or frequency, does not allow visual discrimination. A different color scale is needed. Some scales go up to 2, others up to 5. What do they indicate?

The Seurat package in R was used for this analysis and this visualization strategy is widely used to show how gene expression is distributed within tSNE plots. Overall, gray indicates lower gene expression and red represents higher levels of gene expression. The limits of the scale varies for each gene shown as the scale is automatically set to maximize contrast between low and high gene expression for each gene, to optimize visual discrimination. The color actually depicts Log2(UMIs+1) and this label has been added next to the scales (Figure 6G).

19) Subsection “NK Cells downregulate Eomes during T. gondii infection”, "the numbers of CD49a+ and CD49a+ Ly6C+ cells were significantly reduced in Eomes cKO compared to Eomes f/f controls (Figure 6A,B)." That result is in 6B. Figure 6A is very different, it shows that the frequency of these cells is higher in Eomes cKO. This difference is not explained. In contrast, the experiment with bone marrow chimeras shown in Figure 6D is very clear. Why are changes in the relative cell frequencies so different from changes in cell numbers?

In the figure (Figure 7A), the cells are pregated on CD3 CD19 NK1.1+ NKp46+ cells. As conventional NK cells are absent in Eomes cKO mice, the frequency of NK1.1+ NKp46+ cells that are Ly6C+ CD49a+ is higher, although the cell number does not change. This has been further clarified in the text (subsection “NK cells downregulate Eomes during T. gondii infection”).

20) The columns in Figure 7D are not defined. The corresponding legend is dense. It looks like columns may have been grouped as NK-uninf, NK-inf and ILC1. Does each column represent a different mouse?

The columns are labeled above by color, with each column representing a separate mouse (biological replicates). The labels correspond to the legend shown in Figure 8A, as does the entirety of what is now Figure 8. This was clarified in the figure legend.

21) Subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes”. "NK cells share many epigenetic features…" Share with whom?

We intended to state that NK cells from uninfected mice and NK cells from infected mice share many epigenetic features. This has been clarified (subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes.”).

22) Subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes”. "Somewhat surprisingly" Since T. gondii infection has a large impact on both NK cells and ILC1 cells, why are epigenetic changes common to both populations surprising?

We have deleted “somewhat surprisingly” (subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes.”).

23) Sequencing analysis shows there are two genes for Ly6C. Does the analysis of phenotypes with anti-Ly6C antibody detect both? What is the significance of having two genes?

There are two distinct genes that encode Ly6C (Ly6c1 and Ly6c2). Currently there are no antibodies that are able to distinguish between the two, and there are no known differences in regulation or expression pattern of the two genes. The significance of there being two discrete genes is not known.

24) Subsection “T. gondii infection results in ILC1 expansion.”. A symbol that is neither an "a" nor a Greek letter α appears in "a-NK1.1". What is it? The context suggests it is an antibody that causes depletion of NK1.1+ cells in mice. If so, it should be described. What does the symbol represent? The symbol appeared again on subsection “T. gondii-induced ILC1s are distinct from NK Cells and ILC1s” in "TNFa". It should be replaced by the Greek letter α.

The symbol in “a-NK1.1” was supposed to refer to “anti,” and has been replaced with “anti.” The alpha symbol (α) is now used in TNFα (Introduction, Results section, Discussion section, Materials and methods section and figure legends).

25) Visually, Figure 8—figure supplement 1C does not convey a clear message. How were the subsets defined? What could be their biological relevance?

The groups are explained in the text in subsection “Eomes downregulation within NK cells accompanies extensive transcriptional and epigenomic changes”. To clarify their significance, their definitions were reiterated in the figure legend and representative schematics of each group were added as Figure 8—figure supplement 1D, with corresponding changes to the legend.

26) The two comparisons made from the ATAC-seq analysis in Figure 7G for Eomes and Figure 8—figure supplement 1F for T-bet show small differences. Is there a way to express a statistical significance? The changes do not look convincing.

Indeed, there was one peak in the Tbx21 locus that was incorrectly highlighted. This highlighted peak has been unhighlighted (Figure 8—figure supplement 1F). Otherwise, significantly different peaks were identified using the getDiffExpression program in Homer, using a Log2FC cutoff of 1 and FDR cutoff of 0.05. These details were added to the Materials and methods section. For the reviewers’ reference, zoomed in images showing all biological replicates with the adjusted p-values for comparison of NK cells from infected mice versus ILC1-like cells at the Eomes and Tbx21 loci are provided in Author response image 2.

Author response image 2

27) The legend to Figure 8—figure supplement 1E does not adequately explain the Figure. What does the figure show?

This figure (now Figure 8—figure supplement 1F) incorporates RNA-seq data with ATAC-seq data to correlate gene expression levels to accessibility. For each locus, each differentially accessible peak is symbolized by a point. The position of the bottom point along the y-axis indicates Log2FC of gene expression by RNA-seq, comparing ILC1-like cells with NK cells from infected mice. The shading of each point represents the Log2FC of each peak’s accessibility, again comparing ILC1-like cells with NK cells from infected mice. Details were added to the figure legend to further clarify. This figure is based off of what was shown in “Epigenetic control of innate and adaptive immune memory” by Lau et al., 2018 in their Figure 6B.

https://doi.org/10.7554/eLife.47605.024

Article and author information

Author details

  1. Eugene Park

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Conceptualization, Resources, Data curation, Formal analysis, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2617-7571
  2. Swapneel Patel

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Investigation, Writing—review and editing
    Competing interests
    No competing interests declared
  3. Qiuling Wang

    Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared
  4. Prabhakar Andhey

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Data curation, Formal analysis, Visualization
    Competing interests
    No competing interests declared
  5. Konstantin Zaitsev

    1. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    2. Computer Technologies Department, ITMO University, Saint Petersburg, Russia
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  6. Sophia Porter

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Investigation
    Competing interests
    No competing interests declared
  7. Maxwell Hershey

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Validation, Investigation
    Competing interests
    No competing interests declared
  8. Michael Bern

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Validation, Investigation
    Competing interests
    No competing interests declared
  9. Beatrice Plougastel-Douglas

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Methodology
    Competing interests
    No competing interests declared
  10. Patrick Collins

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Data curation, Formal analysis
    Competing interests
    No competing interests declared
  11. Marco Colonna

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Conceptualization, Resources, Funding acquisition
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5222-4987
  12. Kenneth M Murphy

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Supervision
    Competing interests
    No competing interests declared
  13. Eugene Oltz

    1. Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    2. Department of Microbial Infection and Immunity, Ohio State University Wexner School of Medicine, Columbus, United States
    Contribution
    Resources, Supervision, Methodology
    Competing interests
    No competing interests declared
  14. Maxim Artyomov

    Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Supervision, Methodology
    Competing interests
    No competing interests declared
  15. L David Sibley

    Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, United States
    Contribution
    Resources, Supervision, Methodology
    Competing interests
    No competing interests declared
  16. Wayne M Yokoyama

    Division of Rheumatology, Department of Medicine, Washington University School of Medicine, St. Louis, United States
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Visualization, Writing—original draft, Project administration, Writing—review and editing
    For correspondence
    yokoyama@wustl.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0566-7264

Funding

National Institute of Diabetes and Digestive and Kidney Diseases (F30DK108472)

  • Eugene Park

National Institute of Allergy and Infectious Diseases (AI120606)

  • Eugene Oltz

National Institute of Allergy and Infectious Diseases (AI134035)

  • Marco Colonna
  • Eugene Oltz

National Institute of Allergy and Infectious Diseases (AI11852)

  • Eugene Oltz

National Cancer Institute (CA188286)

  • Eugene Oltz

National Institute of Allergy and Infectious Diseases (AI128845)

  • Wayne M Yokoyama

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

This work was supported by NIH grants F30DK108472 (EP), AI128845 (WMY), AI120606 (EMO), AI134035 (EMO, MC), AI11852 (EMO), and CA188286 (EMO). We thank members of the Yokoyama Lab, Ilija Brizic, Stipan Jonjic, and Victor Cortez for helpful discussions, Jennifer Barks and Reeha Savari Dhason for HFF cells, Nathaniel Jones, Sumit Kumar, Josh Radke, and Kevin Brown for T. gondii strains, Suzanne Hickerson for technical assistance, and Lacey Feigl, Lorraine Schwartz, and Shirley McTigue for administrative assistance.

We thank the Genome Technology Access Center in the Department of Genetics at Washington University School of Medicine for help with genomic analysis. The Center is partially supported by NCI Cancer Center Support Grant #P30 CA91842 to the Siteman Cancer Center and by ICTS/CTSA Grant# UL1 TR000448 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research. This publication is solely the responsibility of the authors and does not necessarily represent the official view of NCRR or NIH.

We also thank the McDonnell Genome Institute, especially Catrina Fronick, Robert Fulton, and Amy Ly, for assistance and advisement regarding genomic analysis.

Ethics

Animal experimentation: All protocols were approved by the Institutional Animal Care and Uses Committee (Washington University School of Medicine, St. Louis, MO) under animal protocol number 20160002.

Senior Editor

  1. Tadatsugu Taniguchi, Institute of Industrial Science, The University of Tokyo, Japan

Reviewing Editor

  1. Alan Sher, NIH, NIAID, United States

Reviewers

  1. Chris Hunter, The University of Pennsylvania
  2. Jinfang Zhu, National Institute of Allergy and Infectious Diseases, National Institutes of Health, United States
  3. Eric O Long, National Institute of Allergy and Infectious Diseases, United States

Publication history

  1. Received: April 11, 2019
  2. Accepted: August 8, 2019
  3. Accepted Manuscript published: August 8, 2019 (version 1)
  4. Version of Record published: August 21, 2019 (version 2)

Copyright

© 2019, Park et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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