SP140 limits type I interferon-driven pathology, preserving T cell motility and promoting resistance in tuberculosis

Maxime Caouaille, Léa Fromont, Tomoyo Shinkawa, Marion Faucher, Aizat

Iman Abdul Hamid, Serge Mazères, Yaël Duvergé, Yohan Lorreyte,

Emmanuelle Näser, Samuel M Behar, et al.

► To cite this version:

Maxime Caouaille, Léa Fromont, Tomoyo Shinkawa, Marion Faucher, Aizat Iman Abdul Hamid, et al. SP140 limits type I interferon-driven pathology, preserving T cell motility and promoting resistance in tuberculosis. 2025. hal-05423835

HAL Id: hal-05423835

https://hal.science/hal-05423835v1

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1 **SP140 limits type I interferon-driven pathology, preserving T cell motility and promoting resistance in tuberculosis**

3 Maxime Caouaille¹, Léa Fromont¹ #, Tomoyo Shinkawa² #, Marion Faucher¹ ³ #, Aizat Iman Abdul

4 Hamid ¹ #, Serge Mazères¹, Yaël Duvergé¹, Yohan Lorreyte¹, Emmanuelle Näser¹, Samuel M Behar²,

5 Emma Lefrançais¹ *, Olivier Neyrolles¹ § and Denis Hudrisier¹ * §

6
7 ¹ Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS,
Toulouse, France

9 ² Department of Microbiology, University of Massachusetts Chan Medical School, Worcester, MA,
10 USA

11 ³ Present address: G.CLIPS Biotech, Labège, France
12
13 #L.F., T.S., M.F., and A.-I.A.-H. contributed equally to the work.

14 * Correspondence: E.L. (Emma.Lefrancais@ipbs.fr); D.H. (Denis.Hudrisier@ipbs.fr).

15 § O.N., and D.H. contributed equally to the work.

17 **Short title:** SP140 restrains IFN-I to preserve CD8⁺ T cell immunity in TB

18
19 **Key Words:** CD8⁺ T cells, Interferon, NETosis, Tuberculosis, SP140
20 Abstract

21 CD8+ T cells are robustly activated during tuberculosis but how their responses differ in susceptible
22 hosts remains unclear. Using mice lacking the transcriptional repressor Sp140, we assessed the
23 magnitude and diversity of pulmonary CD8+ T cell responses to *Mycobacterium tuberculosis* infection.

24 We show that control mice develop a robust CD8+ T cell response following infection, characterized by
25 a diverse pool of effector and memory subsets and strong TNF and IFNγ production, whereas *Sp140*⁻/⁻ mice display a profound reduction in T cell numbers across all subsets. Single-cell RNA sequencing
26 revealed redistribution and skewing of CD8+ T cell clusters in *Sp140*⁻/⁻ mice, with overrepresentation of
27 gene expression programs associated with exhaustion and type I interferon (IFN-I) signaling. Blockade
28 of the IFN-I receptor (IFNAR) restored CD8+ T cell numbers, diversity, cytokine production, spatial
29 localization, and coincided with substantially reduced bacterial burden and lung pathology. Similarly,
30 CD4+ T cell numbers were also rescued. Intravital microscopy of infected lungs further showed that T
31 cell dynamics and motility within lesions were restricted under exuberant IFN-I signaling but fully
32 restored by IFNAR blockade. Together, these findings reveal that SP140 sustains host resistance in
33 mice by restraining IFN-I-driven pathology, coinciding with preserved T cell immunity and lesion
34 surveillance.
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36

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## 37 Introduction

Tuberculosis (TB), caused by *Mycobacterium tuberculosis*, remains a major global health threat, with over 10.5 million new cases and over a million deaths in 2024 (Global Tuberculosis Report 2025). It is estimated that *M. tuberculosis* has infected roughly a quarter of the world's population (Global Tuberculosis Report 2025). Remarkably, only 5-10% of infected individuals develop active TB disease, highlighting the overall effectiveness of human immune defenses against *M. tuberculosis*. Although considerable progress has been made in understanding TB immunity, critical questions remain regarding the mechanisms that mediate protective immune responses. Evidence from human studies and animal models, in particular mice and non-human primates (NHPs), has shown that CD4⁺ T cells are essential for TB control (Kwan and Ernst, 2011; Jasenosky et al., 2015; Flynn and Chan, 2022), and excessive neutrophil recruitment into the lungs is detrimental (Moreira-Teixeira et al., 2020; Branchett et al., 2025; Gern et al., 2025; Kotov et al., 2023). However, variations in CD4⁺ T cell and neutrophil responses do not fully account for differences in disease outcomes, nor has analysis of CD4⁺ T cells provided sufficient predictive or therapeutic value for vaccine development (McShane, 2019; Morgan et al., 2021). Thus, understanding the contributions of additional immune cell subsets to protection against TB remains a key goal.

The role of CD8⁺ T cells in immunity to *M. tuberculosis* infection in mice is more complicated than that of CD4⁺ T cells, and this has been the subject of some controversy over the years. Early studies in mice showed that deficiency of total CD8⁺ T cells (e.g. CD8α⁻/⁻), or of CD8⁺ T cells restricted by classical MHC class I molecules (β2m⁻/⁻), increases susceptibility to *M. tuberculosis* (Mogues et al., 2001; Urdahl et al., 2003; Behar et al., 1999; van Pinxteren et al., 2000); however, antibody-mediated depletion experiments suggested a relatively modest role for conventional CD8⁺ T cells during acute infection (Van Pinxteren et al., 2000; Mogues et al., 2001). By contrast, depletion of CD8⁺ T cells during latent infection in mice or in *M. tuberculosis*-infected old mice increased bacterial
burden in the lungs, whereas depletion of CD4⁺ T cells had little effect (Van Pinxteren et al., 2000; Turner et al., 2002). Studies in NHPs demonstrated the importance of CD8α⁺ cells both in natural immunity and in the protection afforded by intravenous BCG vaccination, an effect that is likely mediated by multiple CD8α⁺ populations, predominantly innate lymphoid cells (Winchell et al., 2023; Simonson et al., 2025; Gideon et al., 2022; Chen et al., 2009). In humans and experimentally infected animals, M. tuberculosis elicits robust CD8⁺ T cell responses that correlate with bacterial control (Balin et al., 2018; Busch et al., 2016; Bruns et al., 2009; Stenger et al., 1998; Dallmann-Sauer et al., 2025; Jalbert et al., 2023; Di Liberto et al., 2007). In addition, adoptive transfer experiments showed that CD8⁺ T cells can restrict M. tuberculosis in vivo (Woodworth et al., 2008). These CD8⁺ T cells contribute to protection through multiple mechanisms, including direct cytotoxicity, cytokine production, and regulation of inflammatory responses. In mice, polyclonal, infection-elicited, CD8⁺ T cells can restrict M. tuberculosis in vitro (Lu et al., 2021) and in vivo (Mogues et al., 2001; Flynn et al., 1992; Woodworth and Behar, 2006; Lai et al., 2024), and vaccine-induced CD8⁺ T cell responses enhance pulmonary TB control (Wu et al., 2008; Mu et al., 2010). Collectively, these studies highlight the contribution of CD8⁺ T cells to optimal control of M. tuberculosis infection (Flynn and Chan, 2022; Behar et al., 2007; Woodworth and Behar, 2006; Behar, 2013; Lazarevic and Flynn, 2002).

CD8⁺ T cells consist of diverse subsets defined by their tissue localization, migratory property, effector functions, and lifespan, including tissue-resident memory, effector, and central memory populations (Laidlaw et al., 2016; Christo et al., 2024; Mueller and Mackay, 2016; Jameson and Masopust, 2018; Schenkel and Masopust, 2014; Shin and Iwasaki, 2013; Szabo et al., 2019; van Gisbergen et al., 2021; Zheng and Wakim, 2022). The contribution of dedicated memory CD8⁺ T cell subsets in various acute and chronic pathologies has been well established (Yenyuwadee et al., 2022; Chung et al., 2021). In TB, although both human and animal studies have demonstrated a protective role for CD8⁺ T cells, the differences in the responses of these cells in susceptible and resistant hosts,
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particularly within the lungs, remain poorly understood. Notably, the ability of CD8+ T cells to traffic to infected lesions and exert effector functions may be shaped by host genetics and the local inflammatory environment, and elucidating how these factors regulate CD8+ T cell responses is important to advance our understanding of TB immunity and potentially to inform novel immunomodulatory strategies.

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A growing body of evidence shows that the inflammatory environment, particularly cytokine signaling and neutrophil activity, plays a critical role in shaping T cell dynamics in TB (Moreira-Teixeira et al., 2020; Smith et al., 2019; Dorhoi et al., 2014; Marzo et al., 2014; Kotov et al., 2023). Type I interferons (IFN-I) in particular have been implicated in TB pathogenesis, with excessive IFN-I signaling associated with worsened disease outcomes in humans (Berry et al., 2010; Zhang et al., 2018) and experimental models (Antonelli et al., 2010; Manca et al., 2001; Kang et al., 2022). Excessive IFN-I signaling has been shown to modulate the relative abundance of immune cells populations in the lungs of TB-infected mice (Moreira-Teixeira et al., 2020; Kinsella et al., 2025; Liu et al., 2025; Chowdhury et al., 2024; Kotov et al., 2023). Two recent studies showed that IFN-I signaling drives a pathological accumulation of neutrophils in lungs of TB-susceptible C3HeB/FeJ mice, precluding the infiltration of protective CD4+ T cells into lesions. Depletion of neutrophils or blockade of IFN-I signaling in these mice reversed the relative abundance of neutrophils and CD4+ T cells in lung lesions and decreased bacterial burden (Gern et al., 2025; Branchett et al., 2025). Notably, CD8+ T cell numbers were also reduced in C3HeB/FeJ mice (Branchett et al., 2025), potentially contributing to their susceptibility to M. tuberculosis. The mechanisms underlying the effects of IFN-I on T cell responses in TB remains incompletely understood.

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The transcription factor Sp140 is a key regulator of IFN-I responses that is associated with immune-mediated diseases and bacterial infection, such as Legionella pneumophila and M. tuberculosis in mice (Kotov et al., 2023; Ji et al., 2021; Amatullah et al., 2022; Witt et al., 2025). Located within the super-susceptibility to tuberculosis-1 (sst1) locus, Sp140 has recently been shown to
restrain IFN-I responses during infection (Kotov *et al.*, 2023; Ji *et al.*, 2021; Amatullah *et al.*, 2022; Witt *et al.*, 2025), with mice lacking *Sp140* exhibiting exacerbated IFN-I production and heightened susceptibility to *M. tuberculosis*—phenotypes that was completely reversed upon genetic ablation of IFN-I signaling (Ji *et al.*, 2021).

Here, we investigate how the inflammatory microenvironment shapes pulmonary CD8⁺ T cell responses during aerosol *M. tuberculosis* infection in mice in the presence and absence of *Sp140*. Using high-dimensional cytometry, single-cell transcriptomics, and intravital imaging, we show that unrestrained IFN-I signaling results in a collapse of CD8⁺ T cell numbers and function and impairs T cell motility within TB lesions in susceptible *Sp140*-deficient mice. Because CD4⁺ T cell numbers were likewise reduced in *Sp140*⁻/⁻ mice and rescued by IFNAR blockade, our findings uncover a previously unrecognized role for Sp140 in safeguarding adaptive immunity by limiting IFN-I-mediated pathology and identify additional IFN-I-dependent barriers that impede T cell dynamics in TB lesions.

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124 **Results**

125 **Profound dysregulation of pulmonary CD8⁺ T cells in *Sp140⁻/⁻* mice.**

126 To investigate the contribution of CD8⁺ T cells during *M. tuberculosis* infection, we compared 127 pulmonary T cell responses in resistant (*Sp140⁺⁺*) and susceptible (*Sp140⁻⁻*) mice following aerosol 128 infection with the Erdman strain of *M. tuberculosis* (Ji *et al.*, 2021). *Sp140⁺⁺* mice survived beyond day 129 56 while *Sp140⁻⁻* mice succumbed to infection before day 28, with uncontrolled bacterial replication 130 and severe lung pathology with necrotic lesions, necessitating euthanasia for ethical reasons 131 (Supplemental Figure 1). Using a 27-antibody spectral flow cytometry panel that included a 132 fluorescently labeled anti-CD45 antibody injected intravenously 5 minutes before sacrifice to 133 distinguish cells residing within the lung parenchyma (CD45iv⁻) from those within the vasculature 134 (CD45iv⁺) (Sakai *et al.*, 2014), we observed a dramatic decrease in the proportion of CD8⁺ T cells in 135 *Sp140⁻⁻* mice between day 21 post-infection and later time points (Figure 1A). Unsupervised analysis 136 revealed a robust diversity of subsets within the CD8⁺ T cell compartment in control mice, which 137 included naïve, activated and memory CD8⁺ T cells, most of which expressed TCRβ and CD8αβ 138 (Supplemental Figure 2). Unsupervised clustering analysis was not possible in *Sp140⁻⁻* mice due to the 139 low numbers of CD8⁺ T cells in the lungs of these mice (Figure 1A).

140 To assess CD8⁺ T cell subsets in *Sp140⁻⁻* mice, we established a gating strategy using both 141 surface and intracellular markers (Supplemental Figure 3) that allowed us to distinguish effector and 142 memory CD8⁺ T cell subpopulations and characterize their kinetics in the lungs over the course of 143 infection. We focused on CD8⁺ T cell subsets with well-characterized roles in various pathological 144 contexts (Christo *et al.*, 2024; Laidlaw *et al.*, 2016; Jameson and Masopust, 2018; Wang *et al.*, 2022), 145 including short-lived effector (SLEC), exhausted (T<sub>EX</sub>), stem cell memory (T<sub>SCM</sub>), central memory 146 (T<sub>CM</sub>), effector memory (T<sub>EM</sub>), virtual memory (T<sub>VM</sub>), and resident memory (T<sub>RM</sub>) cells, with T<sub>EM</sub> cells 147 comprising two subpopulations: “true” T<sub>EM</sub> and peripheral memory T cells (T<sub>PM</sub>) (Gerlach *et al.*, 2016).
We noted a profound reduction in both the number and diversity of CD8+ T cells in *Sp140<sup>-/-</sup>* mice compared with controls. At day 21 post-infection, *Sp140<sup>+/-</sup>* mice harbored a diverse array of activated and memory CD8+ T-cell populations in the lung parenchyma, predominated by SLEC, T<sub>CM</sub>, and T<sub>EM</sub> subsets, with minimal representation by T<sub>EX</sub>, T<sub>RM</sub>, T<sub>SCM</sub>, and T<sub>VM</sub> subsets (Figure 1A). Lungs of *Sp140<sup>-/-</sup>* mice contained significantly fewer CD8+ T cells whereas overall diversity was comparable to that of *Sp140<sup>+/-</sup>* mice at this time point (Supplemental Fig. 4A). Notably, T<sub>EX</sub> cells were significantly enriched in *Sp140<sup>-/-</sup>* mice but virtually absent in *Sp140<sup>+/-</sup>* mice at day 21 (Figure 1B).

The differences in CD8+ T cell composition in the lung parenchyma were more pronounced at later time points, with cell numbers increasing substantially in wild-type mice by day 35 and both CD103+ and CD103- T<sub>RM</sub> cells becoming more prominent (Figure 1A). Within the T<sub>EM</sub> subset in wild-type mice, T<sub>PM</sub> cells predominated within the lung parenchyma, whereas “true” T<sub>EM</sub> cells were more abundant in the pulmonary microvasculature (Supplemental Figure 4B). Consistent with the spectral flow cytometry data, more than 90% of CD8+ T cells in the lungs expressed TCRβ and CD8αβ (Supplemental Figure 4C), corresponding to conventional CD8+ T cells. T cell numbers in *Sp140<sup>-/-</sup>* mice, by contrast, declined between day 21 and day 28, accompanied by a collapse in subset diversity, with nearly all populations disappearing and only a small number of SLEC and T<sub>EX</sub> cells persisting (Figure 1B). Results were similar when analyzing TB10.4-specific CD8+ T cells identified using an H-2K<sup>b</sup>/TB10.4 tetramer (Supplemental Figure 4D and Figure 1C and D) (Billeskov et al., 2007). The CD8+ T cell compartment in the lung vasculature of *Sp140<sup>-/-</sup>* mice showed a similar decrease in numbers and subset diversity as seen in the parenchyma, which was distinct from wild-type mice (Supplemental Figure 4E-F). These results show that although CD8+ T cell responses are effectively initiated and traffic to the lungs in both mouse strains, their numbers are dramatically lower and progressively wane over the course of infection in *Sp140<sup>-/-</sup>* mice.
To measure CD8+ T cell function, we assessed cytokine production after *ex vivo* stimulation with a cocktail of CD4+ and CD8+ T cell antigens on the H-2b background (Supporting Materials and Methods section and Supplemental Figure 5A). In *Sp140<sup>+/+</sup>* mice, multiple parenchymal CD8+ T cell subpopulations produced TNF and/or IFNγ, with T<sub>RM</sub> being the main cytokine producers (Figure 1F and Supplemental Figure 5A and B). As expected, T<sub>EX</sub>, T<sub>CM</sub>, T<sub>VM</sub>, and T<sub>SCM</sub> subsets did not produce cytokines (Supplemental Figure 5A). In the lung vasculature, TNF and IFNγ were mostly produced by SLEC and T<sub>EM</sub> populations (Supplemental Figure 5B). In *Sp140<sup>-/-</sup>* mice, T<sub>EM</sub> and SLEC were the only CD8+ T cell subsets that produced TNF and/or IFNγ at day 21, and cytokine production decreased over time, becoming nearly undetectable by day 28 (Figure 1F, Supplemental Figure 5B and C). Similarly, only modest cytokine production was detected in the vasculature from SLEC and T<sub>EM</sub> cells (Supplemental Figure 5C). Together, these findings reveal a profound dysregulation of the CD8+ T cell compartment in *Sp140<sup>-/-</sup>* mice, with severely decreased cell numbers, collapse of phenotypic diversity, and impaired effector cytokine production. These results indicate that Sp140 is critical for sustaining protective CD8+ T cell responses during TB, and its absence precipitates catastrophic CD8+ T cell failure upon *M. tuberculosis* infection.

CD8+ T cells from *Sp140<sup>-/-</sup>* mice display signatures of type I IFN and exhaustion pathways.

To explore the unexpected differences in CD8+ T cell subpopulation diversity between *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* mice in an unbiased manner, we performed a global scRNA-seq analysis of parenchymal CD8+ T cells to gain deeper insight into their phenotypic and functional heterogeneity and to identify potential mechanisms underlying these disparities. To recover sufficient cells, mice were infected with a lower inoculum (30 CFUs); this diminished the between-strain differences in CD8+ T cell numbers and diversity observed at 100 CFUs (Supplemental Figure 6A), but *Sp140<sup>-/-</sup>* mice still developed severe disease using the lower dose (Supplemental Figure 6B), with markedly decreased CD8+ T cell numbers (Supplemental Figure 6C).
scRNA-seq confirmed substantial heterogeneity among lung-infiltrating CD8⁺ T cells in both genotypes (Figure 2A), with eleven clusters shared across both genotypes but with distinct relative proportions (Figure 2B-D). A small fraction of myeloid cells (cluster 9) was detected but were considered to be contaminants because they lacked CD8 expression (Supporting Information). Functional gene-expression patterns (Figure 2E) revealed an activation continuum across clusters 0–2, with expression of genes associated with activation, polyfunctionality, and exhaustion progressively increasing across clusters. Cluster 0 occurred at similar frequencies in both genotypes, whereas clusters 1 and 2 were enriched in CD8⁺ T cells from *Sp140⁻/⁻* mice (Figure 2B, D). These clusters also expressed high levels of cytokines and cytotoxic molecules, a signature associated both with protective capacity and functional impairment due proteotoxic stress (Wang *et al.*, 2025)—the latter seeming more consistent with our data. As expected, the IFN-I response, concentrated in cluster 5, was enriched in CD8⁺ T cells from *Sp140⁻/⁻* mice, whereas naive-like clusters 4 and 7 were enriched in CD8⁺ T cells from *Sp140⁺/⁺* mice (Figure 2D, E). Cluster 3 exhibited tissue-resident signatures (*Itgae*, *Itga1*), alongside numerous mitochondrial transcripts, consistent with dying or low-quality cells. The presence of *P2rx7* transcripts is compatible with the preferential loss of P2X7R⁺ T<sub>RM</sub> cells under exposure to tissue damage (Table S2) (Stark *et al.*, 2018). Cluster 6 comprised proliferating CD8⁺ T cells, while clusters 8 and 10 contained rare γδ T cells and Tc17 cells (Figure 2A).

To refine cluster identities, we projected published gene-set signatures (Im *et al.*, 2016; Miller *et al.*, 2019; Oliveira *et al.*, 2021) onto our data. Interferon-α, tumor-response, and exhaustion signatures scored highest in clusters 1, 2, and 5, which were overrepresented in CD8⁺ T cells from *Sp140⁻/⁻* mice, suggesting a link between Sp140 deficiency, heightened exhaustion and IFN-I-driven transcriptional programs in CD8⁺ T cells (Figure 2F). Enrichment analyses using external CD8⁺ T cell datasets (Miller *et al.*, 2019) corroborated this conclusion, with *Sp140⁻/⁻* profiles strongly enriched for effector-like, exhaustion, and IFN-I-responsive genes (Figure 2G and supplemental Figure 6D). Reference mapping against CD8⁺ T cell states from acute (Armstrong) versus chronic (clone 13)
220 LCMV infection (Giles *et al.*, 2022) again recapitulated the pattern: *Sp140*⁻/⁻ CD8⁺ T cells aligned with
221 chronic effector-like, exhausted, and ISG states, whereas control cells aligned with acute naïve and
222 effector states (Figure 2H).

223 Pseudotime analysis using Monocle3 further supported this model, positioning clusters 2 and 5
224 at terminal endpoints associated with exhaustion- and IFN-I-enriched programs, respectively (Figure
225 2I). Differential gene-expression and Gene Ontology analyses across the full dataset showed that
226 *Sp140*⁻/⁻ CD8⁺ T cells were skewed toward IFN-I and antiviral response pathways, whereas *Sp140*⁺/⁺
227 cells were enriched for immune-activation and differentiation programs (Figure 2J-K). Collectively,
228 these data reveal profound transcriptional reprogramming of CD8⁺ T cells in the Sp140-deficient
229 environment, driving them toward IFN-I-skewed, exhausted states and providing a mechanistic
230 explanation for the impaired CD8⁺ T cell response observed in *Sp140*⁻/⁻ mice upon *M. tuberculosis*
231 infection.

232 **IFN-I drives deficient responses in both CD8⁺ and CD4⁺ T cells and high bacterial loads in Sp140⁻/⁻ mice.**
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234 IFN-I expression is a hallmark of *Sp140*⁻/⁻ mice infected with *M. tuberculosis* and has been
235 reported to profoundly reshape myeloid cell responses (Kotov *et al.*, 2023; Ji *et al.*, 2021). Consistent
236 with this, several T cell clusters that are unique to, or markedly overrepresented in, *Sp140*⁻/⁻ mice
237 exhibit a strong transcriptional signature typical of a type I IFN response (Figure 2). To evaluate the
238 impact of IFN-I on T cell responses, we administered a blocking anti-IFNAR monoclonal antibody to
239 *Sp140*⁻/⁻ mice. Consistent with previous reports (Dorhoi *et al.*, 2014; Naik *et al.*, 2024; Ji *et al.*, 2019,
240 2021), anti-IFNAR treatment markedly reduced bacterial loads in *Sp140*⁻/⁻ mice at day 28, restoring
241 them to levels comparable to those in *Sp140*⁺/⁺ mice (Figure 3A). This was accompanied by substantial
242 improvement in lung pathology and stabilization of body weight in anti-IFNAR-treated *Sp140*⁻/⁻ mice
243 (Figures 3B-C). Neutrophil extracellular trap formation (NETosis) is amplified by IFN-I and has been
shown to be detrimental in TB infection (Moreira-Teixeira et al., 2020; Kotov et al., 2023; Chowdhury et al., 2024). Histone citrullination (cit-H3), a marker of NETosis, was markedly enhanced in Sp140⁻/⁻ mice but reverted to levels comparable with Sp140⁺/⁺ control mice following anti-IFNAR treatment (Figure 3D). IFNAR blockade also restored CD8⁺ T cell numbers in Sp140⁻/⁻ mice and promoted their infiltration into lung near bacteria-containing lesions (Figure 3D). In marked contrast, CD8⁺ T cells were sparse and remained distant from both bacteria-rich and cit-H3-rich lesions in untreated Sp140⁻/⁻ mice, suggesting that an IFN-I-dominated environment restricts CD8⁺ T cell access to infected sites (Figure 3D). Importantly, IFN-I blockade restored CD8⁺ T cell responses, rescuing both cell numbers and phenotypic diversity (Figure 3E), with similar results observed when gating on M. tuberculosis-specific CD8⁺ T cells (Supplemental Figure 7A). This restoration was evident across both supervised and unsupervised analyses, and in both the lung parenchyma and vasculature (Supplemental Figure 7B-D). Importantly, CD4⁺ T cell underwent the same collapse in Sp140⁻/⁻ mice and were fully restored upon anti-IFNAR treatment (Supplemental Figure 7E). Cytokine production by CD8⁺ T cells was also fully restored following anti-IFNAR treatment (Figure 3F). In contrast, administration of anti-IFNAR to Sp140⁺/⁺ mice had no effect on bacterial loads, body weight loss, or T cell responses (Supplemental Figure 8A-D).

**The type I interferon-dominant environment impairs both CD8⁺ and CD4⁺ T cell mobility within TB lesions.**

The loss of the CD8⁺ T cell response in Sp140⁻/⁻ mice and its restoration following IFNAR blockade (Figures 1 and 3) mirrors previous observations in TB, in which susceptible C3HeB/FeJ mice displayed reduced pulmonary CD4⁺ T cell accumulation after infection with the virulent M. tuberculosis HN878 strain (Branchett et al., 2025). Our scRNA-seq analysis identified an IFN-I responsive CD8⁺ T cell cluster enriched in the lungs of Sp140⁻/⁻ mice (Figure 2), suggesting a potential intrinsic effect on CD8⁺ T cells. To determine whether the IFN-I-mediated inhibition of T cell access to
and motility within lesions involved intrinsic or extrinsic signals (or both), we adoptively transferred labeled CD8⁺ T cells from *M. tuberculosis*-infected *Sp140⁺⁺* donors into *Sp140⁻⁻* recipients (Figure 4A). To optimize transfer timing, we monitored IFN-I-driven tissue damage by tracking the kinetics of cit-H3 accumulation (Supplemental Figure 9A-B), which confirmed T cell exclusion from TB lesions (Branchett *et al.*, 2025). Transfers were performed between days 21 and 28, when IFN-I-dependent pathology was established (Figure 3D). Total CD4⁺ T cells from the same donors were co-transferred at a 1:1 ratio with CD8⁺ T cells to provide helper signals (Lu *et al.*, 2021). Parallel transfers were performed in anti-IFNAR-treated *Sp140⁻⁻* mice, which display reduced inflammation and tissue pathology (Figure 3). Twenty-four hours after transfer, intravital lung imaging was performed to evaluate T cell localization and motility within infected lungs during 60-minute time-lapse acquisitions.

Albeit transferred CD8⁺ T cells successfully reached the lung parenchyma and infiltrated granulomatous lesions in *M. tuberculosis*-infected *Sp140⁻⁻* mice (Figure 4B), they exhibited low velocities and presented arrest coefficients close to 100%, indicating that they were essentially immobile within lesions (Figure 4C and supplemental movie 1). In sharp contrast, CD8⁺ T cells transferred into anti-IFNAR-treated *Sp140⁻⁻* mice efficiently accessed lesions (Figure 4B) and showed higher motility, characterized by longer track lengths and displacement, higher mean and maximum velocities, and a reduced arrest coefficient (Figure 4C and supplemental movie 2). Because CD4⁺ T cells were co-transferred in these experiments (Figure 4A) and have been reported to accumulate poorly within TB lesions in susceptible mice (Branchett *et al.*, 2025; Gern *et al.*, 2025) and to be similarly affected in *Sp140⁻⁻* mice in a IFN-I-dependent manner (our Supplemental Figure 7E), we also analyzed their dynamics. Consistent with the CD8⁺ phenotype, CD4⁺ T cells in untreated *Sp140⁻⁻* mice exhibited minimal motility, whereas anti-IFNAR treatment markedly enhanced all motility parameters (Supplemental Figure 8C-D, Supplemental movies 3 & 4).

Together, these findings demonstrate that type I IFN profoundly impairs T cell immunity in *Sp140⁻⁻* mice by driving exhaustion, and restricting recruitment to and motility within TB lesions. The
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data show that an IFN-I-dominated inflammatory milieu coincides with limited CD8+ and CD4+ T cell

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access to pulmonary lesions *in vivo* but, as shown here for the first time, also restricts their movement

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within these structures, revealing a potentially critical mechanism of immune evasion in TB.

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**Discussion**

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T cells play a central and well-established role in immunity to TB in both humans and animal models. Classically, differences in T cell responses between susceptible and resistant hosts have been evaluated based on functional parameters, such as cytokine production and cytolytic capacity. Because elimination of *M. tuberculosis*-infected cells requires direct contact with T cells (Srivastava and Ernst, 2013), understanding the molecular and spatial determinants of successful T cell access to lesions is critical. This is particularly important considering that T cells exist in various lineages and subsets, displaying not only diverse biological functions but also variable lifetimes, migration and residency patterns, and tissue-positioning properties (Laidlaw *et al.*, 2016; Christo *et al.*, 2024; Mueller and Mackay, 2016; Shin and Iwasaki, 2013; Gasper *et al.*, 2014; Mueller *et al.*, 2013; Woodland and Kohlmeier, 2009).

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Prior work identified *Sp140* as a gene within the murine *sst1* locus that confers resistance to TB by restraining deleterious type I IFN pathways (Ji *et al.*, 2021; Kotov *et al.*, 2023). However, to date, the consequences of *Sp140* deficiency have been mostly studied in innate cells (Ji *et al.*, 2021; Pan *et al.*, 2005).

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Our findings establish that Sp140 deficiency profoundly impairs adaptive immunity during *M. tuberculosis* infection, with both CD8+ and CD4+ T cells excluded from lung lesions in *Sp140*-deficient mice. In *Sp140<sup>+/+</sup>* mice, pulmonary CD8+ T cells expand robustly and differentiate into multiple effector and memory subsets, including T<sub>RM</sub> and T<sub>EM</sub> populations capable of producing cytokines (IFN-γ and TNF) that are associated with protection against TB (Ogongo *et al.*, 2019, 2021; Perdomo *et al.*, 2016; Bull *et al.*, 2019). In contrast, mice lacking *Sp140* showed a collapse the numbers, subset diversity, and cytokine production of CD8+ T cells in the lungs by 3-4 weeks post-infection, with a substantial fraction of CD8+ T cells displaying an exhausted phenotype. Previous studies have shown that
exhaustion of CD4⁺ T cells leads to loss of protection in models of chronic TB infection (Lu et al., 2021; Jayaraman et al., 2016; Chang et al., 2025). The collapse of CD8⁺ and CD4⁺ T cells coincided with extreme susceptibility to TB in *Sp140*⁻/⁻ animals, which develop severe symptoms, including uncontrolled bacterial growth, tissue damage, weight loss and immunopathology. These results confirm that *Sp140* is essential for innate defenses against TB and show that its expression is also essential for preserving T cell immunity, indirectly enabling long-term, T cell-mediated protection against *M. tuberculosis* infection.

Dysregulated IFN-I signaling drives the susceptibility of *Sp140*⁻/⁻ mice (Ji et al., 2019, 2021; Kotov et al., 2023) and underlies the T cell attrition we report here. Single-cell RNA sequencing and phenotypic analysis revealed that *Sp140*-deficient CD8⁺ T cells bear strong IFN-I-induced transcriptional signature and exhaustion programs, which correlate with T cell dysfunction. Several features of these signatures (e.g. upregulation of stemness genes) overlap with those seen in subsets of exhausted CD8⁺ T cells in models of melanoma and chronic viral infection (Im et al., 2016; Miller et al., 2019; Oliveira et al., 2021). The rescue of immunity and reduction in bacterial loads after IFNAR blockade in *Sp140*-deficient mice mirrors prior findings showing that *Sp140*⁻ or *sst1*⁵⁻/⁻ mediated susceptibility to TB is largely driven by IFN-I (Ji et al., 2019). CD4⁺ T cells have a well-established role in immunity to *M. tuberculosis*; however, their abundance does not consistently correlate with protection in TB, indicating that additional immune components contribute to host defense. CD8⁺ T cells are strong candidates, supported by studies in both mice and non-human primates demonstrating context-dependent increases in susceptibility when CD8⁺ T cells are absent or depleted [(Li et al., 2025) and references therein]. Although our current study did not directly assess a requirement for CD8⁺ T cells in the setting of an anti-IFNAR-mediated restoration of bacterial control, future work will incorporate CD8⁺ T cell depletion and targeted reconstitution to determine their necessity and sufficiency in this model.
Excess IFN-I has been shown to undermine host defense in TB by inducing immunosuppressive factors, including IL-10 (McNab et al., 2015) and IL-1Ra (Ji et al., 2019), and by skewing innate responses toward pathological inflammation (Moreira-Teixeira et al., 2020; Kotov et al., 2023; Ji et al., 2021; Naik et al., 2024; Ji et al., 2019; Antonelli et al., 2010; Manca et al., 2001; Kang et al., 2022; Mayer-Barber et al., 2014). Sp140⁻/⁻ mice exhibit hallmarks of IFN-I-driven immunopathology, including a key role for increased neutrophil influx and extensive NET formation, as shown in previous studies (Kotov et al., 2023; Berry et al., 2010; Zhang et al., 2018; Gern et al., 2025). Blocking IFN-I signaling has been shown to reverse essentially all immune defects described in TB-susceptible mouse strains, including reversing the loss of T cells [our study in Sp140⁻/⁻ mice and the study by Naik et al. in Irgm1⁻/⁻ mice (Naik et al., 2024)], and reducing neutrophil accumulation and NETosis in C3HeB/FeJ mice (Kotov et al., 2023; Chowdhury et al., 2024; Branchett et al., 2025), indicating that IFN-I drives both T cell attrition and tissue-damaging innate responses. However, whether elevated bacterial burden and associated pathology, aside from IFN-I signaling, can also constrain T cell numbers and diversity remains untested.

IFN-I are strong and key regulators of CD8⁺ T cell responses exerting complex positive and negative effects on CD8⁺ T cells: they can deliver growth-inhibitory signals or conversely promote survival and clonal expansion of the CD8⁺ T cell pool, depending on the pathogen and/or the effector or memory status of the cells. At the functional level, IFN-I enhance cytotoxicity but can either up- or down-modulate IFN-γ production. Finally by shaping the magnitude of the primary response, IFN-I determine the size, trafficking and effector function of the downstream memory CD8⁺ T cell compartment (McNab et al., 2015; Moreira-Teixeira et al., 2018; Crouse et al., 2015). It therefore came as a surprise that excessive IFN-I production in Sp140⁻/⁻ mice has a profoundly deleterious impact on all CD8⁺ T cells, regardless of their effector or memory status and function. Although our study mainly
focused on CD8+ T cells, we made similar observations for CD4+ T cells, indicating that both arms of the T cell response were curtailed. These mice, like *sst1<sup>S</sup>* mice, have a normal T cell compartment and do not display obvious signs of altered T cell activation at steady-state (Kotov *et al.*, 2023; Yan *et al.*, 2007). Consistent with this, IFN-I-dependent collapse of both CD4+ and CD8+ T cell responses has also been reported in *Irgm1<sup>-/-</sup>* mice (Naik *et al.*, 2024).

Previous studies failed to show a fundamental defect in T cell activation in the lymph nodes of *M. tuberculosis*-infected mice exposed to excess IFN-I either via direct cytokine administration or co-infection with a virus (Antonelli *et al.*, 2010; Kang *et al.*, 2022). Many of the TB lesions present in the lungs have been linked to IFN-I (Chowdhury *et al.*, 2024; Ravimohan *et al.*, 2018; Dorhoi and Kaufmann, 2016) and, in some reports, IFN-I correlated with a reduced presence of T cells in the lungs of *M. tuberculosis*-infected mice (Moreira-Teixeira *et al.*, 2020; Chowdhury *et al.*, 2024; Kang *et al.*, 2022; Branchett *et al.*, 2025).

Together, these findings underscore a scenario in which excess IFN-I creates a hostile environment that alters the T cell compartment. We hypothesized that, in the absence of Sp140, unrestrained IFN-I production results in excessive inflammation and the formation of physical and molecular barriers that prevent T cells from effectively populating and protecting the lung. Yet, interpreting the restoration of endogenous T cell responses in susceptible *Sp140<sup>-/-</sup>* or C3HeB/FeJ mice, treated with anti-IFNAR, is challenging because of the potential effects of altered IFN-I milieu on initial T cell priming and differentiation, and subsequent effects on activation, migration, and survival.

Our data do not allow us to distinguish T cell-intrinsic from extrinsic IFN-I effects on the multiple CD8+ and CD4+ T cell subsets elicited during infection. Our scRNAseq analysis revealed that IFN-I signatures distinguish CD8+ T cells from *Sp140<sup>-/-</sup>* mice suggesting a direct impregnation of these cells by IFN-I. Recent studies show that the predominant IFN-I-dependent effect reported in *Sp140<sup>-/-</sup>* mice may be mediated by IFNAR-
400 expressing myeloid cells (Kotov *et al.*, 2023). T cell-specific perturbation of IFNAR
401 signaling in individual lineages or subsets will be required to fully address this question.
402 Conversely, pSTAT1 or ISG downregulation in T cells after anti-IFNAR could be informative
403 in this regard.

404 Flow cytometry or still imaging can only partially capture key parameters of T cell
405 accessibility and dynamics in the lungs. Intravital imaging, the most appropriate approach to
406 overcome the limitations of still imaging (Lefrançais *et al.*, 2025), is particularly challenging
407 to implement in the context of the lungs, especially in a BSL3 environment (Ueki *et al.*, 2020;
408 Castanheira *et al.*, 2023). By leveraging adoptive T cell transfer and intravital lung imaging,
409 we directly visualized how an IFN-I-rich environment can physically constrain T cells, with
410 dramatically reduced mobility of the transferred cells that were able to penetrate bacterium-
411 rich lesions in *Sp140*⁻/⁻ hosts. In contrast, in anti-IFNAR-treated *Sp140*⁻/⁻ mice treated, T cells
412 migrated freely into the lung parenchyma and accumulated near *M. tuberculosis* foci, closely
413 resembling the behavior of CD4⁺ T cells observed in infected lungs of WT C57BL/6 mice
414 (Fromont *et al.*, 2025). These results are consistent with the recent study of Branchett *et al.*,
415 which demonstrates that IFN-I signaling promotes exclusion of CD4⁺ T cells from lesions
416 (Branchett *et al.*, 2025). Our results extend this concept by revealing that excessive IFN-I
417 signaling not only limits T cell entry into infected areas but also constrains their motility
418 within lesions, which could contribute to the inhibition of effective local anti-TB immunity.

419 These observations align with recent reports that elevated IFN-I signaling can hinder T
420 cell migration in a pleiotropic manner by modulating multiple parameters, such as chemokine
421 production and the tissue microenvironment. For instance, virus-induced IFN-I has been
422 shown to suppress CXCL9 and CXCL10 production by myeloid cells, impairing the
423 pulmonary influx of *M. tuberculosis*-specific Th1 cells (Kang *et al.*, 2022). Additionally, IFN-
424 I-driven inflammation may create structural barriers to T cell entry, such as excessive
425 extracellular matrices or NETs (Kotov *et al.*, 2023; Chowdhury *et al.*, 2024). High levels of
426 citrullinated histones (cit-H3) in the pulmonary lesions in *Sp140*⁻/⁻ mice indicate abundant
427 NET formation, which can trap bacteria but also exacerbate tissue damage (Moreira-Teixeira
428 *et al.*, 2020; Kotov *et al.*, 2023; Chowdhury *et al.*, 2024) and have been shown to correlate
429 with exclusion of CD4⁺ T cells from lesions (Branchett *et al.*, 2025; Gern *et al.*, 2025). Our
430 data confirm that T cells are excluded from infected sites when IFN-I is rampant, a condition
431 reversed by neutralizing this cytokine signaling. In non-human primate, IFN-I-expressing
432 cells surround but do not infiltrate cit-H3⁺ areas (Chowdhury *et al.*, 2024). Since T cells are
433 excluded from cit-H3 areas, whether T cells are in close proximity of IFN-I-producing cells
434 remain to be investigated. Also, imaging T cell positioning respective to local IFN-I
435 concentration in TB lesions was not determined in our study and may help addressing this
436 question. Thus, one key mechanism by which Sp140 enables effective TB immunity is by
437 keeping IFN-I responses in check, ensuring that T cells can navigate to and engage pathogens
438 in the lung tissue. This supports the idea that physical or functional barriers, whose identity
439 yet remains to be fully characterized, undermine the effectiveness of T cell-mediated
440 immunity in TB (Lefrançais *et al.*, 2025).

441 In summary, our study uncovers a critical intersection between innate immune
442 regulation and adaptive immunity in TB. Sp140 emerges as a key host factor that restrains
443 IFN-I-driven pathology, thereby preserving the CD8+ and CD4+ T cell response for optimal
444 control of *M. tuberculosis*. These findings place Sp140 within a growing framework whereby
445 excessive IFN-I signaling is a dominant antagonist of protective TB immunity (Berry *et al.*,
446 2010; McNab *et al.*, 2015; Moreira-Teixeira *et al.*, 2018; Mayer-Barber *et al.*, 2014).
447 Importantly, the parallels between Sp140 deficiency in mice and the elevated neutrophil
448 driven IFN-I gene signature observed in TB patients, which correlates with severe disease and
449 destructive lung pathology (Berry *et al.*, 2010; Zhang *et al.*, 2018), suggest that our results
have direct clinical relevance. This notion is further substantiated by genetic evidence
showing that single-nucleotide polymorphisms in SP140 confer an increased risk of
developing multiple chronic inflammatory diseases in humans [see (Amatullah et al., 2022)
and references therein].

Excessive IFN-I signaling has been proposed to render TB an “atypical
interferonopathy” (Vance, 2025). In this context, our findings highlight the therapeutic
potential of targeting the IFN-I axis to restore host resistance. Transient IFNAR blockade or
inhibition of downstream pathways could re-establish effective T cell functions and bacterial
control in individuals with hyperinflammatory TB. More broadly, this work opens new
directions for modulating the tissue microenvironment of TB lesions to enhance T cell
activity. Future studies aim at defining the molecular “brakes” imposed by IFN-I, whether
through altered chemokine gradients, metabolic suppression, or physical barriers, and
determining how relieving these constraints can improve vaccine efficacy and treatment
outcomes.

464
465 Authors' contributions
466

466
M.C. conducted experiments, analyzed data and wrote the manuscript. L.F. and A.-I.A.-H.
467
performed intravital microscopy experiments. T.S. analyzed the scRNA-seq data of lung
468
CD8+ T cells. M.F. generated fluorescent strains of M. tuberculosis and contributed to in vivo
469
experiments. S.M. designed and built the surgical platform and lung window, coded all in-
470
house Python scripts for cell tracking and behavior analysis, and performed image and movie
471
analyses. Y.D. performed immunofluorescence staining and their quantification. Y.L.
472
characterized the pool of peptides for T cell stimulation. E.N. helped design the antibody
473
panels for spectral cytometry. S.M.B. provided financial support and directed the work of T.S.
474
E.L. supervised, designed, performed and analyzed the intravital microscopy experiments.
475
O.N. secured major funding and provided regular, in-depth scientific guidance, contributing
476
477 to experimental design and key expertise. D.H. supervised the project, designed and analyzed

478 experiments, and wrote the manuscript. All authors critically revised the manuscript.

479

480

481 Acknowledgments

482 We thank Russel Vance for the kind gift of the *Sp140*⁻ mice as well as Geanncarlo Lugo-

483 Villarino and Yoann Rombouts for critical reading of our manuscript. We thank Jérémy

484 Sintes for calibrating the aerosol delivery apparatus and Claude Gutierrez for the conception

485 of plasmids to transform *M. tuberculosis*. We acknowledge the cytometry (Genotoul TRI-

486 IPBS) and animal (Genotoul Anexplo-IPBS) facilities, particularly Flavie Moreau, Malory

487 Blasco and Céline Berrone for technical support. TRI-IPBS is member of the national

488 infrastructure France-BioImaging (https://ror.org/01y7vt929) supported by the French

489 National Research Agency (ANR-24-INBS-0005 FBI BIOGEN); Anexplo-IPBS is member

490 of the national infrastructure Celphedia (https://ror.org/00v2cdz24). This work was supported

491 by Fondation Bettencourt Schueller (Grant Explore-TB to O.N.), ANRS MIE (Contract

492 KILL-TB #206385 to D.H.), the European Commission Horizon Programme (Grant TBVAC-

493 HORIZON #101080309 to O.N. and E.L.), the Fondation pour la Recherche Médicale (Grant

494 Equipe FRM #EQU202103012733 to O.N.), National Institutes of Health (grants

495 1R01AI192333 and R01AI172905 to S.M.B., and grant R21 AI156407 to E.L and O.N.),

496 ANRS MIE (PhD fellowship to L.F. and to M.C.), University of Toulouse (Tremplin 2022

497 #0003970 to E.L.). Figures were created with Biorender.com.

498
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876
877 **Material and methods**

878 **Mice**

879 Male and female mice aged 6-10 weeks were used throughout the study. C57BL/6 ($Sp140^{+/+}$) mice were purchased from Charles River France. $Sp140^{-/}$ mice were kindly provided by Dr.

880 Russel Vance (UC Berkeley, USA) and bred at the Institute of Pharmacology and Structural Biology (IPBS) UMR 5089 (agreement F31555005). All procedures complied with French regulations and were approved by the Ministry of Higher Education and Research (APAFIS agreements 38001, 34716, 47848 and 50470).

885

886 **Bacteria**

887 Fluorescent derivatives of the wild-type *M. tuberculosis* strain Erdman were constructed by transformation of this strain with pGMCS-P1-GFP and pGMCS-P1-mTurquoise. Plasmids pGMCS-P1-GFP and pGMCS-P1-mTurquoise are integrative vectors in mycobacteria that confer resistance to streptomycin and constitutively express GFP or mTurquoise fluorescent reporters, respectively. They were constructed by Gateway cloning, as described previously (Ariyachaokun *et al.*, 2020).

889 *M. tuberculosis* Erdman and its fluorescent GFP or mTurquoise transformants were cultured either in suspension in Middlebrook 7H9 medium (BD) supplemented with 10% albumin-dextrose-catalase (ADC, BD) and 0.05% Tyloxapol (Sigma), or on 7H11 medium supplemented with 10% oleic acid-albumin-dextrose-catalase (OADC, BD). For infection, exponentially growing cultures were centrifuged at 2,301 × g, resuspended in phosphate-buffered saline (PBS; Gibco), and de-aggregated by vortexing with glass beads. Remaining clumps were removed by a low-speed spin (120 × g). Bacterial concentration was estimated by measuring the optical density at 600 nm (OD₆₀₀), and the suspensions were adjusted in PBS for *in vivo* infection.
902 **Mouse infection**

903 Mice were exposed to 0.4 × 10⁴ or 2 × 10⁶ bacteria in an inhalation tower (Buxco Inhalation
904 Exposure System, DSI), which is calibrated to deliver approximately 30 or 100 CFUs,
905 respectively, to the lungs per mouse. At 24 h post-infection, lung homogenates from ≥2 mice
906 were plated to confirm the delivered dose. Bacterial burden was quantified by plating serial
907 dilutions on 7H11 + 10% OADC and incubating for 3 weeks at 37 °C.

908

909 **In vivo treatment**

910 Anti-IFNAR monoclonal antibody (500 µg; Bio X Cell) or isotype control was administered
911 intraperitoneally every 2 days from day 7 to day 27 post-infection. Lungs from untreated,
912 isotype-treated, or anti-IFNAR-treated mice were collected at day 28.

913

914 **Lung harvest and cell isolation**

915 Five minutes before euthanasia, mice received an intravenous injection of anti-CD45
916 monoclonal antibody (5 µg) to distinguish parenchymal (CD45i.v.⁻) from intravascular
917 (CD45i.v.⁺) leukocytes. Mice were anesthetized with isoflurane and euthanized by cervical
918 dislocation. Lungs were aseptically harvested and homogenized in PBS (Difco) using a
919 gentleMACS dissociator (C Tubes, Miltenyi). Homogenates were incubated with DNase I
920 (0.1 mg/mL; Roche) and collagenase D (2 mg/mL; Roche) for 30 min at 37 °C, 5% CO₂,
921 filtered through 70 µm strainers, and centrifuged at 423 × g for 5 min. Red blood cells were
922 lysed (150 mM NH₄Cl, 10 mM KHCO₃, 0.1 mM EDTA, pH 7.2; 5 min), washed,
923 resuspended in Cell Staining Buffer (BioLegend), and filtered through 40 µm strainers.
924

925 **Spectral cytometry staining**

926 Single-cell suspensions were stained in 96-well plates with an MHC-I tetramer loaded with
927 the immunodominant TB10.4 antigen for 1 h at room temperature (RT), washed, and
928 incubated with extracellular antibodies and viability dye for 20 min at RT. Cells were then
929 fixed and permeabilized using the eBioscience™ Foxp3/Transcription Factor Staining Buffer
930 Set (30 min, per manufacturer's instructions), followed by intracellular staining for 30 min at
931 RT. For *M. tuberculosis* inactivation, cells were fixed in 4% paraformaldehyde (Fisher
932 Scientific) for 2 h at RT. Samples were acquired on a Cytek Northern Lights 3L (16V-14B-
933 8R) spectral cytometer (Cytek Biosciences). Spectral unmixing was performed with
934 SpectroFlo (Cytek Biosciences). Conventional analyses were performed in FlowJo v10 (BD),
935 and unsupervised analyses/visualizations were performed in OMIQ (Dotmatics). After data
936 cleaning (PeacoQC), datasets were scaled and subsampled prior to UMAP generation.
937 Clustering was subsequently carried out using FlowSOM.

938

939 **Intracellular cytokine staining**

940 For cytokine detection, lung single-cell suspensions were incubated at 37 °C, 5% CO₂ for 4 h
941 with a pool of *M. tuberculosis*-derived peptides (Table S1) in the presence of anti-CD28
942 (2µg/mL; BioLegend) and monensin (2µM; eBioscience). Cells were then stained, fixed, and
943 permeabilized as described above before intracellular staining.

944

945 **Preparation of OCT-embedded tissues**

946 At designated time points, mice were euthanized by intraperitoneal injection of a lethal dose
947 of sodium pentobarbital. The lungs were inflated with 1 mL of 2% ultrapure agarose and then
948 harvested. Tissues were fixed for 24 h at 4 °C in periodate–lysine–paraformaldehyde (PLP)
949 buffer [0.05 M phosphate buffer, 0.1 M L-lysine (Sigma-Aldrich), 2 mg/mL NaIO₄ (ThermoFisher Scientific), 4% paraformaldehyde; pH 7.4]. Samples were cryoprotected in a sucrose gradient at 4 °C and embedded in optimal cutting temperature (OCT) compound.
950
951
952 Frozen tissues were sectioned at 20 µm on a Leica CM1950 cryostat and mounted on SuperFrost Ultra Plus™ GOLD slides (Epredia).
953

954

955

Tissue preparation for immunofluorescence

956 OCT sections were thawed in Milli-Q water (2 × 10 min, RT). Non-specific binding was blocked for 1 h at RT in PBS containing 5% goat serum (GeneTex), 5% bovine serum albumin (BSA; Euromedex), and 0.2% Triton X-100 (Sigma-Aldrich). Sections were incubated overnight at 4 °C with primary antibodies diluted in PBS + 5% BSA + 0.2% Triton X-100. After washing, secondary antibodies were applied for 4 h at RT, followed by DAPI (5 min; Sigma-Aldrich). Sections were mounted in DAKO Fluorescent Mounting Medium (Agilent) and imaged on a Zeiss LSM 710 confocal microscope. Image processing was performed in ImageJ or QuPath.
957
958
959
960
961
962
963

964

965

Image quantification

966 Quantification of cit-H3 and CD8-positive signals in lung sections from *M. tuberculosis*-infected mice was performed using QuPath. Whole-section images were analyzed using a standardized threshold (Classify, Pixel Classification, Threshold) to classify positive vs. negative pixels. All parameters were held constant across samples.
967
968
969

970

971

Single-cell RNA-seq sample preparation

972 Parenchymal (CD45i.v.⁻) CD8α⁺ T cells were sorted from *Sp140⁺/⁺* mice at day 35 post-infection and *Sp140⁻/⁻* mice at day 28 post-infection (infection dose: 30 CFUs) using a
974 FACSAria Fusion (BD) in a BSL-3 facility. Samples were processed with the Chromium
975 Fixed RNA Profiling workflow (10x Genomics) using the Single Cell Fixed RNA Sample
976 Preparation Kit, following the manufacturer's protocol. Briefly, cells were incubated in
977 fixation buffer (1x Fix & Perm Buffer; 4% formaldehyde in nuclease-free water) for 24h at 4
978 °C, centrifuged (850 x g, 5 min, 4 °C), resuspended in 1x quenching buffer, and
979 supplemented with 0.1 volume of preheated Enhancer (10x Genomics PN-20000482).
980 Nuclease-free glycerol was added to 10% (final), and samples were stored at -80 °C prior to
981 sequencing (Single Cell Discoveries, Utrecht, Netherlands).

982

983 scRNA-seq data processing and analysis

984 All downstream analyses were performed using Seurat (v4.1.1) for R (v4.2.0). Genes
985 detected in fewer than 3 cells, or cells with fewer than 200 or more than 7500 genes detected
986 were excluded from analysis of the Sp140<sup>+/+</sup> and Sp140<sup>-/-</sup> CD8<sup>+</sup> T cell datasets. Cells with
987 >10% of transcripts originated from the mitochondria were deemed low-quality and excluded.
988 The TCR genes (Tra[vjc], Trb[vdjc]) were removed to avoid any TCR gene-driven bias
989 during clustering. Log-normalization by the NormalizeData function was performed and the
990 top 2000 highly variable genes were determined using the FindVariableFeatures function.
991 Samples from the Sp140<sup>+/+</sup> and Sp140<sup>-/-</sup> CD8<sup>+</sup> T cell datasets were then merged using the
992 SelectIntegrationFeatures, FindIntegrationAnchors, and IntegrateData function. After data
993 scaling by ScaleData function, Principal Component Analysis (PCA) was performed using the
994 RunPCA function. The optimal number of principal components (PCs) for downstream
995 analysis was determined using an elbow plot and the first 15 PCs were selected. RunUMAP
996 was performed and cells were clustered using FindNeighbours and FindClusters functions (res
997 = 0.4). The cluster markers were found using the FindAllMarkers function (min.pct = 0.25,
998 assay = "RNA"), and avg_log2 fold change (FC) and adjusted *p* value for top30 markers for

999 each cluster are shown in Table S2. Barplot was visualized by dittoseq (v1.10.0).

1000

1001 **Gene signature scoring**

1002 The AddModuleScore function in Seurat (v.4.1.1) was used to compute average gene

1003 expression scores for published gene sets (Table S3).

1004

1005 **Differentially expressed gene analysis**

1006 Differentially expressed genes (DEGs) between *Sp140<sup>+/+</sup>* versus *Sp140<sup>-/-</sup>* CD8<sup>+</sup> T cells were

1007 identified using the FindMarkers function (Table S4). Volcano plots were created with the R

1008 package EnhancedVolcano (v1.16.0). We used the *enrichGO* function in the *clusterProfiler*

1009 package (v4.6.2) to measure the enrichment of modules in GO terms across all three

1010 ontologies ("BP," "MF," and "CC").

1011

1012 **Projection of our scRNA-seq data to published scRNA-seq datasets**

1013 The Run.ProjecTILs function in the ProjecTILs (v.3.3.0) was used to project our scRNA-Seq

1014 dataset onto processed scRNA-Seq data from the following sources: ref_TILAtlasmouse_v1

1015 (https://figshare.com/articles/dataset/ProjecTILs_murine_reference_atlas_of_tumor-

1016 infiltrating_Tells version 1/12478571?file=41398167) and GSE199565.

1017

1018 **Pseudotime trajectory analysis**

1019 Pseudotime was calculated using the Monocle3 (v.1.3.1) package. Using the SeuratWrappers

1020 (v.0.3.0) package, the integrated Seurat object was converted into a cell dataset object. Only

1021 activated classical CD8<sup>+</sup> T cells (Seurat cluster 1-3,5) were retained for the pseudotime

1022 trajectory analysis. A cell with the highest expression level of the *Lef1* and *Sell* genes was set
1023 as the root node. Cells were clustered with *clusterells using “Leiden” as a cluster_method.

1024 Genes of interest were ordered along pseudotime using the plotells_in_pseudotime function.

1026

1027 Lung multiphoton intravital imaging

1028 Lung multiphoton intravital microscopy (MP-IVM) under BSL3 conditions was used to
1029 monitor T cell dynamics, employing a dedicated surgical platform that enables mouse surgery
1030 and transfer within the BSL-3 environment, as well as a lung window specifically adapted for
1031 imaging lesions, as described (Fromont et al., 2025). Briefly, Sp140-/- mice infected 20-28
1032 days earlier with mTurquoise-expressing M.tuberculosis and treated or not with anti-IFNAR
1033 received an adoptive transfer of fluorescently labeled CD8+ and CD4+ T cells. Donor T cells
1034 were magnetically isolated from infected Sp140+/+ mice using anti-CD8 or anti-CD4
1035 microbeads (MojoSort kit, Biolegend) and labeled with either Deep Red or CellTraceTM
1036 Orange. Equal number of CD8+ and CD4+ T cells were mixed 1:1 (2 x 10⁶ each) prior to
1037 transfer. Due to laser excitation wavelength and filters emission configuration, Deep Red-
1038 labeled cells were robustly detected and tracked, whereas CellTrace Orange-labeled cells
1039 were only faintly detectable and used to confirm engraftment. After 24 hours, mice were
1040 anesthetized with ketamine/xylazine (105/3 mg/kg, intraperitoneal), followed by
1041 subcutaneous injections of buprenorphine (0,1 mg/kg) and Ringer Lactate (10 mL/kg).
1042 Dextran, either Texas Red 70,000 MW (1250 µg, D1864 Invitrogen) or Cascade Blue 10,000
1043 MW (1250 µg, D1864 Invitrogen), (50 µL of 25 mg/mL; Life Technologies) was
1044 administered intravenously before imaging to visualize vasculature. Mice were intubated for
1045 mechanical ventilation, and isoflurane (1%) was delivered during imaging. Two ribs were
1046 transected to allow the installation of a lung window over the lesion. Once transferred in the
1047 heated microscope isolator, suction (20-25 mmHg) was applied to gently immobilize the lung
against the coverslip (Dexter Medical 0-250 mbar) of the window. MP-IVM was performed using a Trimscope II Miltenyi Biotec (LaVision Biotec) upright multi-photon microscope equipped with a 20×/1.0 water immersion objective and a Ti-Sapphire femtosecond laser, Chameleon-Ultra II (Coherent Inc.) tuned to 820 nm. Emission signals corresponding to mTurquoise/Cascade Blue, FITC, CTO/Texas Red and Deep Red signals were collected in separate channels using 450/50, 525/50, 595/40 and LP650 filters, respectively. Four channel images were acquired at a rate of ~1 frame per second for 405 × 405 µm field of view at a resolution of 512 × 512 pixel. Multi-tile three-dimensional time-lapse sequences of lesions were recorded for 30 minutes to 2 hours, with Z-stacks collected approximately every minute.

## T cell tracking analysis and motility parameters

Three-dimensional multi-tile videos were stitched and converted into 2D maximum intensity projections for cell tracking. Quantification of T cell dynamics were performed as previously described using Trackmate plugin in ImageJ (National Institutes of Health) and Imaris 9.3.1 software (Oxford Instruments) (Fromont *et al.*, 2025). For each tracked cell, track length, displacement, instantaneous, average and maximum speed were quantified. The arrest coefficient, defined as the percentage of time during which a cell's instantaneous speed remained below 2 µm/min, was also calculated. Lesions were delineated based on the remodeled and tortuous dextran-labeled vasculature in infected regions and the presence of mTurquoise-expressing *M. tuberculosis*.

## Statistical analysis

Sample sizes (*n*), statistical tests, and significance thresholds are indicated in the figure legends. Analyses were performed in Prism 10.0 (GraphPad). Depending on the experiment, either an unpaired ANOVA or an unpaired Student's t-test was used, as specified in the figure
legends. Significance thresholds were *p* < 0.05 (*), *p* < 0.005 (**), *p* < 0.0005 (***), and *p* < 0.0001 (****).

## Legend to Figures

**Figure 1.** Profound dysregulation of pulmonary CD8⁺ T cells in *Sp140<sup>-/-</sup>* mice. *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* mice were infected by aerosol route with 100 CFUs of the Erdman strain of *M. tuberculosis* and, at the indicated time points, were sacrificed and their lungs analyzed by flow cytometry.

A. UMAP representation of live lung cells based on spectral cytometry data, with CD8 expression displayed as a continuous color scale. Samples include equal numbers of cells from *Sp140<sup>+/+</sup>* (days 21 (n=5) and 35 (n=5)) and *Sp140<sup>-/-</sup>* (days 21 (n=5) and 28 (n=5)) mice. Quantification of the CD8-expressing cell cluster is shown (right). Each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. Non parametric Mann-Whitney test was used.

B. Absolute numbers of the main parenchymal lung CD8⁺ T cell subsets in *Sp140<sup>+/+</sup>* mice at days 21 (n=11, mean number of total CD8⁺ T cell: 100,184), 35 (n=12, mean number of total CD8⁺ T cell: 368,332), and 56 (n=11, mean number of total CD8⁺ T cell: 296,671) post-infection. Stacked (left) and individual subpopulations (right) representations are shown. Each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. Data are pooled from two independent experiments, and unpaired two-way ANOVA tests with Tukey correction were used.

C. As in B) for *Sp140<sup>-/-</sup>* mice at days 21 (n=8, mean number of total CD8⁺ T cell: 52,775) and 28 (n=10, mean number of total CD8⁺ T cell: 13,906) post-infection.

D. As in B) but for parenchymal TB10.4-specific CD8⁺ T cell subsets in *Sp140<sup>+/+</sup>* mice at days 21 (mean number of total TB10.4-specific CD8⁺ T cell: 6,257), 35 (mean number of total TB10.4-specific CD8⁺ T cell: 21,047), and 56 (mean number of total TB10.4-specific
1099 CD8⁺ T cell: 22,494) post-infection. Stacked (left) and individual subpopulations (right)
1100 representations are shown.

1101 **E.** As in D) but for *Sp140*⁻/⁻ mice at days 21 (n=8, mean number of total CD8⁺ T cell: 2,388)
1102 and 28 (n=10, mean number of total CD8⁺ T cell: 1,587) post-infection. The color code for
1103 individual CD8⁺ T cell subsets, presented below, is common to all panels B-E.

1104 **F.** Absolute numbers of total lung parenchymal CD8⁺ T cells and CD8⁺ T cell subpopulations
1105 producing IFNγ, TNFα, or both after stimulation with *M. tuberculosis* peptides. Data for
1106 *Sp140*⁺/⁺ mice are shown at days 21 (n=11), 35 (n=12), and 56 (n=11) (left) and for *Sp140*⁻/⁻
1107 mice at days 21 (n=8) and 28 (n=10) (right). Bars and error bars indicate the mean ± standard
1108 deviation.

1109

1110 **Figure 2.** CD8⁺ T cells from *Sp140*⁻/⁻ mice display signatures of type I IFN and
1111 exhaustion pathways. **A.** UMAP visualization of scRNAseq data of lung CD8⁺ T cells from
1112 *Sp140*⁺/⁺ and *Sp140*⁻/⁻ mice infected with *M. tuberculosis* for 35 and 28 days, respectively.

1113 **B.** A stacked bar plot depicts the cluster distribution in CD8⁺ T cells from *Sp140*⁺/⁺ and *Sp140*⁻/⁻ mice.

1115 **C.** Distribution of CD8⁺ T cells from *Sp140*⁺/⁺ (blue) and *Sp140*⁻/⁻ (red) mice on the UMAP.

1116 **D.** A stacked bar plot depicts the sample distribution in CD8⁺ T cells from *Sp140*⁺/⁺ (blue)
1117 and *Sp140*⁻/⁻ (red) mice.

1118 **E.** Dot plot of selected function-associated genes among the CD8⁺ T cell clusters.

1119 **F.** Violin plots depict the enrichment score of indicated CD8⁺ T cell signatures from
1120 published studies, and UMAP is colored based on the enrichment scores.

1121 **G.** Dot plot showing the enrichment scores of indicated CD8⁺ T cell signatures from
1122 published studies in CD8⁺ T cells from *Sp140*⁺/⁺ and *Sp140*⁻/⁻ mice.
1123 **H.** Dot plot showing the enrichment score of IFN-I response in individual cluster of CD8⁺ T cells from *Sp140⁺⁺* and *Sp140⁻⁻* mice.

1125 **I.** Single-cell trajectories constructed using Monocle3. UMAP shows cells colored by pseudotime values along the trajectory (pink line). Clusters 6, 9, and 10 are excluded from the analysis.

1128 **J.** Volcano plot of DEGs between CD8⁺ T cells from *Sp140⁺⁺* and CD8⁺ T cells from *Sp140⁻⁻* mice. Genes with log2FC >0.5 and an adjusted p value < 0.01 are designated by a blue-filled circle.

1131 **K.** GSEA of differentially expressed genes in CD8⁺ T cells from *Sp140⁻⁻* (left) versus CD8⁺ T cells from *Sp140⁺⁺* (right) mice cells with log2FC>0.5 and adjusted P value < 0.01 using MSigDB immunologic signature gene sets (C7). Adjusted P values are denoted in the bar.

1134

1135 **Figure 3.** IFN-I drives deficient responses in both CD8⁺ and CD4⁺ T cells and high bacterial loads in *Sp140⁻⁻* mice. *Sp140⁻⁻* mice infected with 100 CFUs of the Erdman strain of *M. tuberculosis* were treated with or without a blocking mAb against IFNAR between days 7 and 27 post-infection, and then their lungs were collected and analyzed. Untreated *Sp140⁺⁺* mice were used for comparison.

1140 **A.** Pulmonary bacterial loads at 28 days post-infection in *Sp140⁺⁺* (n=5), untreated *Sp140⁻⁻* (n=4), and anti-IFNAR-treated *Sp140⁻⁻* mice (n=10). A representative experiment is shown. Each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. One-way ANOVA tests with Tukey correction was used.

1144 **B.** Weight monitoring from day 0 to day 21 in the same groups of mice. Body weight was monitored over time and expressed as a percentage of the initial body weight (baseline set to
1146

100%). The shaded area corresponds to the standard deviation. One-way ANOVA tests with

1147

Tukey correction was used at day 21.

1148

C. Representative hematoxylin and eosin staining of lung sections (20 µm) from untreated and anti-IFNAR-treated *Sp140*⁻/⁻ mice at 28 days post-infection. Scale bar, 1000 µm.

1149

1150

D. Representative confocal images of lung sections (20 µm) from *Sp140*⁺/⁺ mice (day 35 post infection, left), untreated *Sp140*⁻/⁻ mice (day 28 post infection, middle), and anti-IFNAR-treated *Sp140*⁻/⁻ mice (day 28 post infection, right) infected with *M. tuberculosis*-GFP (bacterial foci indicated by white arrows). CD8⁺ T cells are shown in red, NETs (citrullinated histone H3) in yellow, and nuclei (DAPI) in white. Scale bar, 500 µm. Quantification of NETs and CD8⁺ T cell areas is shown (right). Each data point corresponds to measurements taken from distinct microscopic fields of view from at least 3 different mice per group. One-way ANOVA tests with Tukey correction was used.

1151

1152

1153

1154

1155

1156

1157

1158

E. Representation in absolute numbers of the main parenchymal lung CD8⁺ T cells subpopulations induced during *M. tuberculosis* infection of *Sp140*⁺/⁺ (n=5, mean number of total CD8⁺ T cell: 498,063) and *Sp140*⁻/⁻ treated (n=10, mean number of total CD8⁺ T cell: 338,597) or not (n=4, mean number of total CD8⁺ T cell: 15,119) with anti-IFNAR on day 28. Stacked representation (left) and individual subpopulation (right) are shown. Bars and error bars indicate the mean ± standard deviation. Two-way ANOVA tests with Tukey correction was used.

1159

1160

1161

1162

1163

1164

1165

F. Proportion of IFNγ, TNFα, or both producing lung parenchymal CD8⁺ T cells and main producing CD8⁺ subpopulations after stimulation with *M. tuberculosis* peptides of *Sp140*⁺/⁺ (n=5) and *Sp140*⁻/⁻ treated (n=10) or not (n=4) with anti-IFNAR on day 28. A representative experiment is shown alongside two independent ones. Bars and error bars indicate the mean ± standard deviation.

1166

1167

1168

1169

1170
1171 **Figure 4.** The type I interferon-dominant environment impairs both CD8⁺ and CD4⁺ T
cell mobility and access to TB lesions.

1173 A. Schematic representation of the adoptive transfer and lung live imaging experiment.
1174 Briefly, both lung CD8⁺ and CD4⁺ T cells were isolated from infected Sp140⁺/⁺ mice, labelled
1175 and adoptively transferred into Sp140⁻/⁻ recipient mice treated or not with anti-IFNAR. Lung
1176 intravital imaging was performed 24 hours post-transfer.

1177 **B.** Representative intravital microscopy images of lungs from *M. tuberculosis*-mTurquoise-
1178 infected mice. Bacteria appear in green, transferred CD8⁺ T cells are in magenta, and lesion
1179 boundaries, identified by dextran staining and *M. tuberculosis* fluorescence, are outlined by a
1180 dotted line. Images show *Sp140*⁻/⁻ mice (day 21 post infection, top) and anti-IFNAR-treated
1181 *Sp140*⁻/⁻ mice (day 28 post infection, bottom). The first frame of the video is shown (left),
1182 with corresponding CD8⁺ T cell tracks over the full acquisition period (right). Scale bar, 200
1183 µm.

1184 C. Quantification of CD8⁺ T cell motility parameters during intravital imaging. Each dot
1185 represents a single tracked transferred CD8⁺ T cells. Parameters include track length,
1186 displacement, arrest coefficient (% of of time T cell instantaneous speed < 2 µm/min), and
1187 mean and maximum velocity. Non parametric Mann-Whitney test was used.

1188 **D.** As in C, but for CD4⁺ T cells. Between 30 and 80 individually tracked T cells from seven
1189 untreated *Sp140*⁻/⁻ mice and three anti-IFNAR-treated *Sp140*⁻/⁻ mice.

1190
1191

1192
1193 **Legend to Supplemental Figures**

1194

1195 **Supplemental Figure 1 (related to Figure 1). Bacterial loads and pathology in *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* mice infected with *M. tuberculosis*. *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* mice were exposed to the aerosol route with 100 CFUs of the Erdman strain of *M. tuberculosis*, and at the indicated time points, they were sacrificed, and their lungs were collected.

1199 **A.** Representative hematoxylin and eosin staining of lung sections (20 µm) from *Sp140<sup>+/+</sup>* mice at day 35 post-infection (bacterial loads shown for days 21 (n=11), 35 (n=12), and 56 (n=11)). Each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. CFUs data are pooled from two independent experiments, and unpaired two-way ANOVA tests with Tukey correction were used. Histological images are representative of at least two independent experiments. Scale bar, 1000 µm.

1205 **B.** Same for *Sp140<sup>-/-</sup>* mice at day 28 post-infection (bacterial loads shown for days 21 (n=8) and 28 (n=10)).

1207

1208 **Supplemental Figure 2 (related to Figure 1). Unbiased analysis of spectral cytometry data describing CD8<sup>+</sup> T cells from *Sp140<sup>+/+</sup>* mice infected with *M. tuberculosis*. *Sp140<sup>+/+</sup>* were exposed to the aerosol route with 100 CFUs of the Erdman strain of *M. tuberculosis* and were sacrificed at day 35 post-infection, and their lungs were collected. **A.** UMAP, performed using OMIQ, of the CD3<sup>+</sup>CD8<sup>+</sup> cells and represented using a density plot. **B.** Clustering performed using FlowSOM algorithm of the populations presented in **A**. **C.** UMAP representation with the expression of the indicated markers displayed as a continuous color scale.

1216
1217 **Supplemental Figure 3 (related to Figure 1). Gating strategy to analyze CD8⁺ T cells in Sp140⁺⁺ and Sp140⁻⁻ mice infected with M. tuberculosis.** After excluding doublets, the live cells isolated from the lungs of infected mice are first separated based on the expression of CD3 and CD45i.v., which allows us to analyze parenchymal T lymphocytes (CD45i.v.⁻) compared to vascular T lymphocytes (CD45i.v.⁺). The CD4 vs CD8 staining enables us to focus on CD8⁺ T cells. The various effector cells (short-lived effector cells, SLEC), memory cells (central memory, TCM; effector memory, TEM; resident memory CD103⁺ and CD103⁻, TRM; virtual memory, TVM; stem cell memory, TSCM), and exhausted cells (TEX) are identified using the indicated surface markers.
1226

1227 **Supplemental Figure 4. (related to Figure 1). Further CD8⁺ T cell subset definition and vascular subsets in Sp140⁺⁺ and Sp140⁻⁻ mice infected with M. tuberculosis.**

1229 **A.** Normalized CD8⁺ T cell diversity at day 21 in Sp140⁺⁺ and Sp140⁻⁻ mice. Bars and error bars indicate the mean ± standard deviation.

1231 **B.** Representation of TEM (CX3CR1⁺) and TPM (CX3CR1int) proportion in CD69⁻ CD44⁺ CD62L⁻ CD8⁺ T cells in parenchyma (left) and vasculature (right). Quantification of each subpopulation is shown on the right. Each data point corresponds to one individual Sp140⁺⁺ mouse (n=18). Bars and error bars indicate the mean ± standard deviation. One-way ANOVA test with Tukey correction was used.

1236 **C.** Representation of CD3⁺TCRβ⁺ and CD3⁺TCRβ⁻ (on gated CD3⁺ cells) and CD8αα/CD8αβ (on gated CD8α⁺ cells).

1238 **D.** Same for TB10.4-specific CD8⁺ T cells in parenchyma (left) and in vasculature (right).

1239 **E.** Absolute numbers of the main vascular lung CD8⁺ T cell subsets in Sp140⁺⁺ mice at days 21 (n=11, mean number of total CD8⁺ T cell: 67,566), 35 (n=12, mean number of total CD8⁺ T cell: 103,377), and 56 (n=11, mean number of total CD8⁺ T cell: 46,972) post-infection.
1242 Stacked (left) and individual subpopulations (right) representations are shown. Each data
1243 point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard
deviation. Data are pooled from two independent experiments, and unpaired two-way
1244 ANOVA tests with Tukey correction were used.
1245

1246 F. As in D) but for *Sp140*⁻/⁻ mice at days 21 (n=8, mean number of total CD8⁺ T cell: 11,600)
1247 and 28 (n=10, mean number of total CD8⁺ T cell: 2,084) post-infection.

1248 The color code for individual CD8⁺ T cell subsets in panels A, E, and F is identical to that
1249 used in Figure 1.

1250
1251 **Supplemental Figure 5 (related to Figure 1). Cytokine production by CD8⁺ T cells in**
1252 **Sp140⁺/⁺ and Sp140⁻/⁻ mice infected with M. tuberculosis.**

1253 **A.** Expression of IFNγ and TNFα after *M. tuberculosis* peptide stimulation on CD8⁺ T cell
1254 subsets on day 56 infected *Sp140⁺/⁺* mice.

1255 **B.** Proportions of lung parenchymal CD8⁺ T cells producing either or both IFNγ and TNFα,
1256 after stimulation with *M. tuberculosis* peptides. Data for *Sp140⁺/⁺* mice are shown at days 21
1257 (n=11), 35 (n=12), and 56 (n=11) (left) and for *Sp140⁻/⁻* mice at days 21 (n=8) and 28 (n=10)
1258 (right). Bars and error bars indicate the mean ± standard deviation.

1259 **C.** Absolute numbers of IFNγ, TNFα, or both producing lung parenchymal CD8⁺ T cells and
1260 main producing CD8⁺ subpopulations after stimulation with *M. tuberculosis* peptides. Data
1261 for *Sp140⁺/⁺* mice are shown at days 21 (n=11), 35 (n=12), and 56 (n=11) (left) and for
1262 *Sp140⁻/⁻* mice at days 21 (n=8) and 28 (n=10) (right). Bars and error bars indicate the mean ±
standard deviation.
1263

1264
1265
1266 **Supplemental Figure 6 (related to Figure 2).** scRNAseq analysis of CD8⁺ T cells from
1267 *Sp140⁺⁺* and *Sp140⁻⁻* mice infected with *M. tuberculosis*.

1268 **A.** CD8⁺ T cell diversity in *Sp140⁻⁻* mice (n=15) infected with 30 CFUs of *M. tuberculosis*,
1269 analyzed as in Figure 1A-D. The color code for individual CD8⁺ T cell subsets is identical to
1270 that used in Figure 1.

1271 **B.** Bacterial loads and weight loss in *Sp140⁻⁻* mice (n=8) infected with 30 CFUs of *M. tuberculosis* (to be compared with Supplemental Figure 1 and Figure 3A-B). For CFUs data, each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. One-way ANOVA tests with Tukey correction was used. For weight monitoring, each dot represents the mean weight at the indicated time point, and the shaded area corresponds to the standard deviation.

1277 **C.** Gating strategy used to sort CD45i.v⁻ CD8⁺ T cells from infected *Sp140⁺⁺* (top 5 panels)
1278 and *Sp140⁻⁻* (lower 5 panels) mice for scRNA-seq and percentages of CD8⁺ T cells from both
1279 genotypes (right). Each dot represents a mouse used as a source of CD8⁺ T cells for sorting,
1280 and an unpaired Mann-Whitney t-test was used for statistical analysis.

1281 **D.** CD8⁺ T cells from *Sp140⁺⁺* or *Sp140⁻⁻* mice projected onto CD8⁺ T cells from an LCMV
1282 infection dataset (GSE199565).

1283
1284 **Supplemental Figure 7 (related to Figure 3).** Impact of IFNAR blockade on pathology
1285 and T cell responses in *Sp140⁺⁺* and *Sp140⁻⁻* mice infected with *M. tuberculosis*.

1286 **A.** Representation in absolute numbers of the main parenchymal TB10.4-specific CD8⁺ T cell
1287 subsets induced during *M. tuberculosis* infection of *Sp140⁺⁺* (n=5, mean number of total
1288 TB10.4-specific CD8⁺ T cell: 37,991) and *Sp140⁻⁻* treated (n=10, mean number of total
1289 TB10.4-specific CD8⁺ T cell: 40,962) or not (n=4, mean number of total TB10.4-specific
1290 CD8⁺ T cell: 4,759) with anti-IFNAR on day 28. Stacked representation (left) and individual
1291 subpopulation (right) are shown. Each data point corresponds to one individual mouse. Bars
1292 and error bars indicate the mean ± standard deviation. Unpaired two-way ANOVA tests with
1293 Tukey correction were used. A representative experiment is shown alongside two independent
1294 ones.

1295 **B.** As in A, but for vascular CD8⁺ T cell subsets. *Sp140⁺/⁺* (n=5, mean number of total CD8⁺
1296 T cell: 152,646) and *Sp140⁻/⁻* treated (n=10, mean number of total CD8⁺ T cell: 176,559) or
1297 not (n=4, mean number of total CD8⁺ T cell: 5,283) with anti-IFNAR on day 28

1298 **C.** As in A, but for vascular TB10.4-specific CD8⁺ T cell subsets. *Sp140⁺/⁺* (n=5, mean
1299 number of total TB10.4-specific CD8⁺ T cell: 14,205) and *Sp140⁻/⁻* treated (n=10, mean
1300 number of total TB10.4-specific CD8⁺ T cell: 25,612) or not (n=4, mean number of total
1301 TB10.4-specific CD8⁺ T cell: 1,424) with anti-IFNAR on day 28.

1302 The color code for individual CD8⁺ T cell subsets in panels A-C is identical to that used in
1303 Figure 1.

1304 **D.** UMAP representation of live lung cells based on spectral cytometry data, with CD8
1305 expression displayed as a continuous color scale. Samples include equal numbers of cells
1306 from *Sp140⁺/⁺* and anti-IFNAR-treated or not *Sp140⁻/⁻* mice. Quantification of the CD8-
1307 expressing cell cluster is shown (right). Bars and error bars indicate the mean ± standard
1308 deviation. Unpaired one-way ANOVA tests with Tukey correction were used.

1309 **E.** As in D but for CD4 expression.

1310

1311 **Supplemental Figure 8 (related to Figure 3).** Impact of IFN-I on T cells from mice
1312 infected with *M. tuberculosis*. *Sp140⁺/⁺* and *Sp140⁻/⁻* mice were infected with 100 CFUs of
1313 the Erdman strain of *M. tuberculosis* and treated between days 7 and 27 post-infection with
1314 either an isotype control or a blocking monoclonal antibody (mAb) against IFNAR. Lungs
1315 were collected and analyzed at day 28 post-infection.
1316 **A.** Pulmonary bacterial loads at 28 days post-infection in isotype-treated-*Sp140<sup>+/+</sup>* (n=5), anti-IFNAR-treated *Sp140<sup>+/+</sup>* (n=5), isotype-treated *Sp140<sup>-/-</sup>* (n=5) and anti-IFNAR-treated *Sp140<sup>-/-</sup>* mice (n=5). Each data point corresponds to one individual mouse. Bars and error bars indicate the mean ± standard deviation. One-way ANOVA tests with Tukey correction were used.

1321 **B.** Weight monitoring from day 0 to day 26 in the same groups of mice. Body weight was monitored over time and expressed as a percentage of the initial body weight (baseline set to 100%). The shaded area corresponds to the standard deviation. One-way ANOVA tests with Tukey correction were used at day 26.

1325 **C.** UMAP representation of live lung cells based on spectral cytometry data, with CD8 expression displayed as a continuous color scale. Samples include equal numbers of cells from *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* (isotype or anti-IFNAR treated) mice. Quantification of the CD8-expressing cell cluster is shown (bottom). Unpaired ANOVA tests with Tukey correction were used for statistical analysis.

1330 **D.** As in C but for CD4 expression.

1331
1332 **Supplemental Figure 9 (related to Figure 4). Imaging T cell positioning and mobility in**
1333 *M.tuberculosis*-infected lungs.

1334 **A.** Representative confocal images of lung sections (20 µm) from *Sp140<sup>+/+</sup>* and *Sp140<sup>-/-</sup>* mice, infected with *M. tuberculosis*-GFP. NETs (citrullinated histone H3) in yellow, T cells (CD3<sup>+</sup>) in red and nuclei (DAPI) in white are shown at day 7 (left), day 14 (middle), and day 21 (right) post infection. Scale bar, 500 µm.

1338 **B.** Associated quantification of the NETs area is shown (top) and T cell exclusion form bacteria lesions (right). Briefly, polygons were drawn around the bacterial foci and, using the "expand annotation" tool in QuPath, they were sequentially extended by a radius of 30µm,
1341 40µm, and 50µm. Quantification of NETs and CD3⁺ T cell areas is shown (right). Each data
1342 point corresponds to measurements taken from distinct microscopic fields of view from at
1343 least 2 different mice per group.

1344 C. Representative intravital microscopy images of lungs from *M. tuberculosis*-mTurquoise-
1345 infected mice. Bacteria appear in magenta, transferred CD4⁺ T cells are in red, and lesion
1346 boundaries, identified by dextran staining and *M. tuberculosis* fluorescence, are outlined by a
1347 dotted line. Images show *Sp140*⁻/⁻ mice (day 28 post infection, top) and anti-IFNAR-treated
1348 *Sp140*⁻/⁻ mice (day 27 post infection, bottom). The first frame of the video is shown (left),
1349 with corresponding CD4⁺ T cell tracks over the full acquisition period (right). Scale bar, 200
1350 µm.

1351

1352

1353 **Legend to Supplemental Movies**

1354

1355

1356 **Supplemental Movie 1. Arrested CD8⁺ T cell migration in Sp140⁻/⁻ mice.** Lung intravital
1357 microscopy reveals severely restricted migratory behavior of CD8⁺ T cells in Sp140⁻/⁻ mice.
1358 Multiphoton intravital imaging was performed in *M. tuberculosis*-infected Sp140⁻/⁻ mice (day
1359 21 post-infection) following adoptive transfer of DeepRed⁺ CD8⁺ T cells (magenta). The lung
1360 vasculature is visualized using FITC-dextran (grey), and bacteria are identified by
1361 mTurquoise expression (green). A multi-tile, three-dimensional time-lapse of a lesion was
1362 acquired over 1 hour, with Z-stacks collected approximately every minute. Scale bar, 200 µm.

1363

1364 **Supplemental Movie 2. Restored CD8⁺ T cell migratory dynamics in anti-IFNAR-**
1365 **treated Sp140⁻/⁻ mice.** Lung intravital microscopy shows that anti-IFNAR treatment restores
1366 dynamic CD8⁺ T cell migration within lesions in Sp140⁻/⁻ mice. Multiphoton intravital
1367 imaging was performed in *M. tuberculosis*-infected Sp140⁻/⁻ mice (day 28 post-infection)
1368 treated with anti-IFNAR following adoptive transfer of DeepRed⁺ CD8⁺ T cells (magenta).

1369 The lung vasculature is visualized using FITC-dextran (grey), and bacteria are identified by
1370 mTurquoise expression (green). CD8⁺ T cell motility was tracked over a multi-tile, three-
1371 dimensional time-lapse sequence of lesions. Scale bar, 200 µm.

1372 **Supplemental Movie 3. Arrested CD4⁺ T cell migration in Sp140⁻/⁻ mice.** Lung intravital
1373 microscopy reveals severely restricted migratory behavior of CD4⁺ T cells in Sp140⁻/⁻ mice.

1374 Multiphoton intravital imaging was performed in *M. tuberculosis*-infected *Sp140*⁻/⁻ mice (day
1375 28 post-infection) following adoptive transfer of DeepRed⁺ CD4⁺ T cells (magenta). The lung
1376 vasculature is visualized using FITC-dextran (grey), and bacteria are identified by
1377 mTurquoise expression (green). A multi-tile, three-dimensional time-lapse of a lesion was
1378 acquired over 1 hour, with Z-stacks collected approximately every minute. Scale bar, 200 µm.

1379
1380 **Supplemental Movie 4. Restored CD4⁺ T cell migratory dynamics in anti-IFNAR-**
1381 **treated Sp140⁻/⁻ mice.** Lung intravital microscopy shows that anti-IFNAR treatment restores
1382 dynamic CD4⁺ T cell migration within lesions in *Sp140*⁻/⁻ mice. Multiphoton intravital
1383 imaging was performed in *M. tuberculosis*-infected *Sp140*⁻/⁻ mice (day 27 post-infection)
1384 treated with anti-IFNAR following adoptive transfer of DeepRed⁺ CD4⁺ T cells (magenta).
1385 The lung vasculature is visualized using FITC-dextran (grey), and bacteria are identified by

1386 mTurquoise expression (green). CD4⁺ T cell motility was tracked over a multi-tile, three-
1387 dimensional time-lapse sequence of lesions. Scale bar, 200 µm.

1388
1389
1390
<figure><img src="image_2.png" /><figcaption>A</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>B</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>C</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>D</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>E</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>F</figcaption></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /><figcaption>Figure 1</figcaption></figure>
<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>

<figure><img src="image_17.png" /></figure>

<figure><img src="image_18.png" /></figure>

<figure><img src="image_19.png" /></figure>

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

<figure><img src="image_23.png" /></figure>

<figure><img src="image_24.png" /><figcaption>Figure 2</figcaption></figure>
<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>

<figure><img src="image_27.png" /></figure>

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

DAPI M. tuberculosis CD8 cit-H3

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>
<figure><img src="image_33.png" /></figure>

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<figure><img src="image_36.png" /><figcaption>Figure 4</figcaption></figure>