Acute peritonitis-induced adipose CD127^+ ILC1s express PD-L1 and ameliorate inflammation in mice

Domain: neuroscience
Published: 2026-02-05
Editorial outcome: major_revision

Abstract
Peritonitis is an inflammation of the peritoneum primarily caused by gut perforation and consequent bacterial leakage, a known cause of sepsis. Although adipose tissue is recognized as an immunologically active organ, the involvement of adipose tissue innate lymphoid cells (ILC) in regulating peritonitis remains poorly understood. Here, we employ a cecal ligation and puncture mouse model and demonstrate that circulating CD127− group 1 ILC (ILC1) migrate into the mesenteric adipose tissue (MAT) during the inflammatory period of peritonitis. CD127− ILC1s undergo phenotypic changes to become CD127+ ILC1s, resulting in an increased number of CD127+ ILC1s in the MAT. We also show that this population of CD127+ ILC1s expresses PD-L1, exhibits low IFN-γ production, and potentially acts as a negative regulator of TNF production by γδ T cells, thereby controlling acute peritonitis. Our findings suggest that MAT-CD127+ ILC1s play an important regulatory role in acute peritonitis and may represent a potential therapeutic target for sepsis.

Introduction
Peritonitis is an inflammation of the peritoneum caused by bacterial leakage from an intestinal perforation, leading to a severe acute inflammatory response. If peritonitis is not well controlled, it can progress to sepsis, leading to what remains a high mortality rate of 19.7% as of 20171–3. Despite advances in medical care, there are no definitive treatments to prevent the progression from peritonitis to sepsis. Thus, new perspectives are needed to understand early-stage inflammation in peritonitis and to develop effective immune-based therapies.

Recent studies have shown that adipose tissue, classically recognized as an energy storage organ, contains numerous immune cells; thus, it is considered an important immune organ4,5. Clinical observations have shown that mesenteric adipose tissue (MAT) accumulates at the site of intestinal perforation, indicating its role in immune regulation during acute peritonitis. However, the mechanisms by which MAT regulates immune responses during the acute inflammatory phase of peritonitis are poorly understood and require further study.

Since the discovery of innate lymphoid cells (ILC), their involvement in various diseases through the production of specific cytokines by the five subsets—ILC1s, ILC2s, ILC3s, LTi, and NK cells—has been widely studied, but their potential immunological role during peritonitis, a trigger of sepsis, remains unclear6,7. Initially, ILCs were considered fundamentally tissue-resident, but recent evidence suggests that circulating ILCs may also be involved in the regulation of inflammation. However, research into the nature of circulating ILCs and their links to disease has only recently commenced, and thus, there is a lack of insights into their involvement even during severe systemic inflammatory states such as peritonitis. In addition, recent findings suggest that ILCs interact with helper T cells, not only through cytokine-mediated interactions but also directly via cell surface molecules. The programmed cell death protein 1 (PD-1) and programmed cell death 1 ligand 1 (PD-L1) pathway plays a critical role in immune escape and functions as an immune checkpoint inhibitor for T cells8. Although the interactions between ILC2s or LTi-ILC3s and T cells through cell surface molecules have already been reported9,10, definitive evidence for PD-L1 expression on ILC1s and their regulatory mechanisms on T cells remains largely unknown. Furthermore, while γδ T cells are known to be associated with innate immunity, how ILCs affect these cells remains poorly understood. Thus, clear evidence is needed to fill this gap in our understanding of these immune interactions.

Here, we report a immune mechanism in which MAT-ILC1s express PD-L1 and potentially suppress TNF production by γδ T cells thereby controlling acute inflammation in peritonitis. Our data suggest that spleen-derived ILC1s migrate toward the MAT and implicate a CXCR3/CXCL10 axis in this process. Our findings provide important insights for adipose tissue-targeted therapeutic strategies for peritonitis/sepsis in clinical settings.

Results
Involvement of MAT-ILC1s in CLP-induced acute peritonitis
To clarify the role of ILC in MAT during acute peritonitis, we first analyzed mice subjected to CLP, a commonly used in vivo model of sepsis11. After CLP surgery, the mice had a decreased rectal temperature at 6 hours (CLP 6h) compared to sham-operated control mice (sham control), which normalized by 24 hours (CLP 24h) (Fig. 1A, B, Supplementary Fig. 1A). Consistent with this, disease severity scores indicated worsened pathology at CLP 6h (Supplementary Fig. 1B). Meanwhile, these mice exhibited a low mortality rate (<20%) even 7 days after CLP (Fig. 1C), indicating that our CLP mice could be used as a recovery model with the strongest inflammatory condition occurring at around 6h post-CLP among the examined timepoints. Consistent with these physiological findings, the expression of inflammatory genes Il1b and Il6 was upregulated in the MAT at CLP 6h (Fig. 1D). Furthermore, elevated IL-6 protein levels were detected in both the MAT and plasma at CLP 6h, corresponding to the peak inflammatory timepoint (Fig. 1E, F, and Supplementary Fig. 1C). Additional inflammatory mediators, GM-CSF and S100A8, which are known to be involved in septic conditions12,13, were also upregulated in the MAT (Fig. 1E). In addition, similar trends were observed in the production of inflammatory chemokines, including CCL2, CCL4, CCL5, CCL11, CXCL1, and CXCL10, in the MAT at CLP 6h (Supplementary Fig. 1D), indicating that the MAT could attract numerous immune cell types during acute peritonitis.

We next assessed whether ILCs are involved in the acute peritoneal inflammation induced at CLP 6h in the MAT. Each ILC subset was first characterized in the innate population according to the expression of NK1.1, ST2 (IL-33R), EOMES, GATA3, and RORγt, respectively (Supplementary Fig. 1E)14. NK cells, which share characteristics with ILC1s, were clearly distinguished based on the level of EOMES expression15 (Supplementary Fig. 1E). Notably, the number of ILC1s significantly increased at CLP 6h, concomitant with the peak of inflammation. In contrast, NK cells and ILC2s were unchanged compared to sham controls, and ILC3s were virtually absent at all time points examined (Fig. 1G). In contrast, granzyme B-expressing cytotoxic NK cells were significantly increased at CLP 24h, suggesting a role for NK cells in the resolution phase of CLP-induced MAT inflammation (Supplementary Fig. 1F). No significant changes in the numbers of NK cells and any ILC subset were detected in sham-operated mice at 6 and 24 hours (Supplementary Fig. 1G).

These findings suggest that ILC1s in the MAT are associated with acute inflammation initiated by bacterial leakage after CLP and might be involved in regulating pathogenesis in acute peritonitis.

Identification of CD127-expressing ILC1s with a unique phenotype in MAT during acute peritonitis
Previous studies have indicated that CD127, a marker commonly expressed by all ILC subsets, is lost from tissue-resident ILC1s in the white adipose tissue16–18. In agreement with these reports, a low level of CD127 expression was detected in the sham control (Fig. 2A–C). Surprisingly, however, we observed a marked upregulation of CD127 expression on the ILC1s in the MAT at CLP 6h (Fig. 2A–C). This finding suggests the involvement of MAT-ILC1s with the unique phenotype of high CD127 expression in the early phase of acute peritonitis. At 24 hours post-CLP, CD127⁺ ILC1s persisted at a lower level, while CD127− ILC1s significantly decreased, suggesting that a subset of ILC1s remained in the MAT but exhibited altered phenotypic characteristics (Supplementary Fig. 2A).

A previous study using single-cell RNAseq analysis reported changes in the immune cell profile of white adipose tissue after CLP surgery19, however, ILC1s in the MAT have not been specifically investigated. Therefore, to further characterize the unique phenotype of MAT-ILC1s appearing during acute peritonitis, we performed CITE-seq analysis, which enables simultaneous detection of both gene and cell-surface protein expression20. By integrating ILC1 gene expression data with sham control and CLP 6h from the MAT, we identified four distinct clusters based on their transcriptional profiles (Fig. 2D, E, and Supplementary Fig. 2B). According to the phenotypes and gene expression characteristics, clusters 0 and 1 expressed Tbx21 but had low expression of Gzmb and Eomes (Fig. 2E). In addition, both clusters displayed high expression of NK1.1 and CD49a (also known as integrin α1) proteins, which are known to be expressed on ILC1s (Supplementary Fig. 2C), supporting the identification of these clusters as ILC1s15,21. Within these clusters, Il7r gene expression and CD127 protein levels were high in cluster 0, but lower in cluster 1 (Fig. 2D, E, and Supplementary Fig. 2C). Therefore, we defined cluster 0 as CD127+ ILC1s and cluster 1 as CD127− ILC1s. Similarly, clusters 2 and 3 were identified as NK cells based on their expression levels of Gzmb and Eomes (Fig. 2E), as well as surface expression of KLRG1, a marker of NK cells, and low expression of CD49a and CD127 proteins (Supplementary Fig. 2C). Intriguingly, cluster 0, defined as MAT-CD127+ ILC1s, exhibited lower Ifng expression, whereas cluster 1 showed higher Ifng expression (Fig. 2E), along with distinct variations in inflammation-related gene expression between conditions (Supplementary Fig. 2D). Previous studies have indicated that ILC1s in the adipose tissue can produce much higher amounts of IFN-γ than NK cells and play a crucial role in metabolic disorders16,17. We, therefore, assessed IFN-γ protein expression in MAT-ILC1s by comparing the sham control and CLP 6h. Notably, CD127+ ILC1s in the MAT exhibited reduced IFN-γ production, even under the acute inflammatory condition at CLP 6h, compared to the CD127− ILC1s in both sham and CLP 6h (Fig. 2F–I). A direct comparison at CLP 6h further confirmed that IFN-γ production was more restricted in the CD127⁺ ILC1 subset (Fig. 2H, I).

These findings indicate that during acute peritonitis, ILC1s increasing in the MAT exhibit a unique CD127 high expression phenotype with limited IFN-γ production.

Directed migration of Ly6C-expressing ILC1s from the spleen to the CXCL10-rich MAT
We next asked how the unique MAT-CD127+ ILC1s increased in the MAT during acute peritonitis. Given that ILC1s accumulating at CLP 6h exhibited a high level of CD127 expression, we assessed whether IL-7 production in the MAT affects CD127 expression in relation to inflammation status. Notably, IL-7 production was reduced in the MAT of mice at CLP 6h and 24h compared with that in the sham control (Supplementary Fig. 3A). Furthermore, treatment of mice with recombinant IL-7 (rIL-7) decreased the CD127+ ILC1s and increased the CD127− ILC1s population in the MAT at CLP 6h (Fig. 3A–C). These findings are consistent with previous reports showing that the expression level of CD127 on T cells is flexibly regulated by the presence of IL-7, which functions as a T cell growth factor22,23. These results thus suggest that low CD127 expression on ILC1s is maintained by the presence of IL-7 under homeostatic conditions in the MAT, and that this regulator state is disrupted during acute inflammation.

Meanwhile, if the level of CD127 expression on ILC1s was merely altered by IL-7, we would expect the total number of ILC1s to remain unchanged between sham control and CLP 6h. We, however, found a significant increase in the total number of ILC1s in the MAT of mice with CLP, while the number of CD127− ILC1s was unchanged (Fig. 2C). To determine whether this increase was driven by local proliferation or by cell migration, we next examined Ki-67 expression, a widely used marker of cell proliferation. Ki-67 expression was decreased in CD127− ILC1s following CLP treatment, whereas CD127+ ILC1s showed no significant change at CLP 6h compared with sham controls, but gradually increased during the course of inflammation, with a significant elevation observed at CLP 24h (Supplementary Fig. 3B). These results suggest that local proliferation is unlikely to be a major contributor to the accumulation of MAT-ILC1s at CLP 6h. To further assess the mechanisms underlying the increase in ILC1s, we next addressed ILC1s migration by performing heterochronic parabiosis, which allowed us to trace immune cell migration via the shared blood circulation between surgically connected mice (Fig. 3D)24. In this experiment, migration of CD45.1+ ILC1s from the intact mice was detected in mice expressing CD45.2 in the CLP-inflamed MAT (Fig. 3E, F), indicating that ILC1s infiltrate the MAT of mice during acute inflammation. Furthermore, we also found strong expression of Ly6C, known to be expressed on circulating ILC1s25, by ILC1s isolated from both the MAT and spleen under the sham and CLP 6h conditions, but not from the mesenteric lymph nodes (MLN) (Fig. 3G). Based on these findings, we hypothesized that splenic Ly6C+ ILC1s migrate into the MAT during acute peritonitis. To test this, we performed an adoptive transfer experiment, in which spleen-derived Lin⁻ cells from CD45.2⁺ donor mice were intravenously transferred into CD45.1+ recipient mice (Fig. 3H). The percentage of donor-derived splenic ILC1s that migrate into the MAT was significantly higher in CLP mice compared to sham controls, while a decreasing trend was observed in the spleen (Fig. 3I, and Supplementary Fig. 3C, D). In addition, splenic transplantation using CD45 congenic strains demonstrated a clear enrichment of donor spleen-derived ILC1s within the recipient MAT at CLP 6h (Supplementary Fig. 3E–G). Collectively, these findings suggest that the spleen serves as one of the sources of ILC1s migrating into the MAT during the early phase of acute peritonitis.

Because splenic ILC1s showed a phenotype similar to MAT-ILC1s with high CD127 expression at CLP 6h (Supplementary Fig. 3H, I), we next analyzed splenic ILC1s by focusing on Ly6C expression. Interestingly, we observed robust Ly6C expression in the splenic CD127− ILC1s compared to CD127+ ILC1s regardless of the inflammation state (Fig. 4A). Furthermore, the number of splenic Ly6C+ CD127− ILC1s was greatly reduced at CLP 6h (Fig. 4B and Supplementary Fig. 3J). These results indicate that splenic Ly6C+ CD127− ILC1s migrated out of the spleen via chemotaxis at CLP 6h and corroborate the significant upregulation of several chemokines in the MAT at CLP 6h (Supplementary Fig. 1D). A previous study has shown that ILC1s express CXCR3, a chemokine receptor that mediates cell migration toward its ligand CXCL1026. Since potent CXCL10 expression was observed in the MAT at CLP 6h (Supplementary Fig. 1D), and CXCR3 expression was detected in ILC1s from the spleen, MAT, and MLN (Supplementary Fig. 3K), we further evaluated CXCR3 expression in splenic CD127− ILC1s, along with Ly6C expression. The level of CXCR3 on CD127− ILC1s was higher in the Ly6C+ ILC1s than in splenic Ly6C− ILC1s under the sham condition (Fig. 4C, D). To further assess the role of CXCR3 in this process, we analyzed mice treated with a CXCR3-neutralizing antibody (Fig. 4E). In the isotype control group at CLP 6h, we observed a correlation trend between the splenic ILC1s and MAT-ILC1s, which was lost following CXCR3 blockade (Supplementary Fig. 3L). This disruption indicates that CXCR3-dependent migration from the spleen to the MAT was inhibited. Consistent with this, the number of Ly6C+ CD127− ILC1s in the spleen was significantly elevated following CXCR3 blockade, whereas the Ly6C+ CD127+ ILC1s were unchanged at CLP 6h (Fig. 4F). Together, these observations suggest that splenic Ly6C⁺ CD127⁻ ILC1s migrate to the MAT during peritonitis.

Since increased circulating Ly6C+ ILC1s have been reported in infection models25, we assessed blood ILC1s during peritonitis. Blood ILC1s showed a tendency to increase at CLP 6h (Supplementary Fig. 4A). These circulating ILC1s exhibited low CD127 expression (Supplementary Fig. 4B, C), and notably, the proportion of Ly6C⁺ cells within CD127− ILC1s increased at CLP 6h (Supplementary Fig. 4D). These observations further support the notion that Ly6C⁺ CD127− ILC1s migrate from the circulation into the MAT during acute peritonitis.

Upregulation of PD-L1 on MAT-CD127+ ILC1s at CLP 6h
Since MAT-CD127+ ILC1s in mice at CLP 6h exhibited less IFN-γ production during inflammation (Fig. 2F–I), we next attempted to identify the key factors, other than IFN-γ, regulating inflammation in the MAT within cluster 0, identified as MAT-CD127+ ILC1s (Fig. 2D, E). According to the differential gene expression analysis, Cd274, the gene encoding PD-L1, was elevated in cluster 0 compared with clusters 1–3, together with the upregulation of the Pdcd1lg2 genes (Fig. 5A). Indeed, the intensity of PD-L1 expression was highly upregulated in MAT-CD127+ ILC1s at CLP 6h compared to CD127− ILC1, whereas the level of PD-L1 on NK cells was considerably lower (Fig. 5B, C). In accordance with this, the frequency and absolute number of PD-L1-expressing CD127+ ILC1 were also greatly increased in CLP 6h (Fig. 5D–F). These results suggest that CD127+ ILC1s could contribute to immune regulation during peritonitis via PD-L1 expression.

Regulation of γδ T cells by PD-L1-expressing CD127+ ILC1s
Since PD-1 is widely expressed on T cell subsets during septic inflammation27, we considered the possibility that ILC1s might affect T cells through the PD-1/PD-L1 pathway. Next, we isolated clusters of T cells, ILC1s, and NK cells from the datasets obtained by CITE-seq of MAT-CLP 6h, and the data were applied to ligand-receptor pair analysis28. This approach revealed nine clusters according to differential gene expression: Ccr7-expressing T cells (Ccr7_T), Tbx21-expressing T cells (Tbx21_T), Foxp3-expressing T cells (Foxp3_T), NK cells, CD127-expressing ILC1s (CD127_ILC1), NKT cells, Ifng-expressing ILC1s (Ifng_ILC1), Cd8a-expressing T cells (Cd8_T), and Trdc-expressing γδ T cells (Trdc_T) (Fig. 6A and Supplementary Fig. 5A, B). Subsequently, we found that Trdc-expressing γδ T cells were strongly associated with CD127_ILC1 through the PD-1/PD-L1/L2 pathway in the MAT of mice with CLP 6h (Fig. 6B). Consistent with this finding, large numbers of γδ T cells, but not other T cell subsets, were observed with high PD-1 intensity in the MAT of mice with CLP 6h (Fig. 6C, D, Supplementary Fig. 5C). Accordingly, to validate the impact of PD-1 on γδ T cells in the MAT during acute peritonitis, PD-1 signaling was blocked by injecting a PD-1-neutralizing antibody (Fig. 6E). Adipose tissue-derived γδ T cells are known to be potent producers of IL-17 and TNF, consistent with our CITE-seq data (Supplementary Fig. 5A). We found that γδ T cells produced TNF, with levels significantly increased in the MAT at CLP 6h compared to the isotype control group (Fig. 6F, G). In contrast, IL-17A production by γδ T cells showed no difference between groups (Fig. 6G). These findings suggest that TNF production by γδ T cells in the MAT at CLP 6h is regulated through PD-1 signaling.

Next, we analyzed γδ T cells, with a particular focus on TNF production. We found that the total number of γδ T cells in the MAT remained unchanged across conditions. However, the frequency of TNF-producing γδ T cells was suppressed at both 6 and 24 hours after CLP treatment (Supplementary Fig. 5D). T cells and Macrophages are known to produce TNF during inflammatory phases29. To further assess the dynamics of TNF production in the MAT during the course of acute peritonitis, we analyzed changes in TNF-producing cells population. We found that the total number of TNF⁺ T cells and F4/80⁺ cells remained unchanged, although TNF⁺ T cells showed a trend toward an increase after CLP (Supplementary Fig. 5E, left and 5F). However, within the TNF⁺ T-cell compartment, the proportion of γδ T cells decreased after CLP treatment (Supplementary Fig. 5E, right). These findings suggest that γδ T cells are preferentially suppressed among TNF-producing cells in the MAT following CLP, supporting the notion that γδ T cells are a potential target of PD-L1+ ILC1s.

Suppression of CLP-induced acute inflammation by MAT-ILC1s through inhibition of γδ T cells in the MAT
To obtain more direct evidence of the interaction between γδ T cells and MAT-ILC1s, we generated ILC1-deficient (ILC1 KO) mice to determine the effect of ILC1s in CLP-induced inflammation. Since ILC1 development is known to be regulated by the transcription factor T-bet, and Ncr1 (also termed NKp46) serves as a surrogate marker for ILC1/NK cells, we crossed Ncr1 green Cre mice with Tbx21-floxed mice to generate ILC1 KO mice (Ncr1 green Cre Tbx21 flox/flox)30. In these mice, the deletion of T-bet under the control of NKp46 effectively ablated ILC1s without affecting NK cells in the MAT at CLP 6h (Supplementary Fig. 6A, B). Interestingly, although the total number of γδ T and PD-1-expressing γδ T cells was not altered (Supplementary Fig. 6C, D), loss of ILC1s affected PD-1 expression on γδ T cells in the MAT at CLP 6h (Supplementary Fig. 6E, F).

Next, we used ILC1 KO mice to ask whether the absence of ILC1s affects the function of γδ T cells and regulates local inflammation during peritonitis. Notably, mice lacking ILC1s clearly exhibited lower body temperature, especially in the early inflammatory phase at CLP 6h (Fig. 7A). Furthermore, the decreased survival of ILC1-deficient mice after CLP surgery indicated that excessive inflammation was induced during acute peritonitis and that ILC1s were involved (Fig. 7B). In support of the in vivo phenotype (Fig. 7A, B), TNF production by γδ T cells was increased in the absence of ILC1s compared to the genetic control at CLP 6h, while no change in IL-17 production was detected (Fig. 7C–E), consistent with the results from PD-1/PD-L1 blockade (Fig. 6F, G). In addition, the expression of pro-inflammatory genes such as Lep (encoding Leptin, one of the pro-inflammatory adipokines), Il1b, and Lcn2, as well as levels of TNF and IL-1β protein in the MAT, and Lipocalin-2 in plasma, were all upregulated in the MAT lacking ILC1s at CLP 6h (Fig. 7F–H). These findings suggest that ILC1s prevent the exacerbation of MAT inflammation.

Finally, to confirm the functional relevance of TNF signaling, we administered a TNF inhibitory mAb to ILC1 KO mice and assessed disease severity at CLP 6h (Fig. 7I). Compared to genetic controls and untreated ILC1 KO mice, the anti-TNF-treated ILC1 KO groups showed attenuated disease severity, as indicated by lower disease scores (Fig. 7J). Furthermore, the expression of the inflammation-associated gene Lcn2 was elevated in ILC1 KO mice, whereas it remained low in the anti-TNF-treated group, comparable to levels observed in wild-type controls (Fig. 7K). These findings suggest that ILC1-mediated suppression of TNF production is essential for controlling and promoting disease resolution during peritonitis.

Additionally, we generated bone marrow (BM) chimeric mice lacking PLZF, a transcription factor essential for ILC1s development. To avoid systemic defects caused by global PLZF deficiency, BM cells from PLZF−/− or PLZF+/+ CD45.2⁺ donor mice were transferred into irradiated CD45.1⁺ wild-type recipients (Supplementary Fig. 7A). In PLZF−/− BM chimeric mice, ILC1s, ILC2s, and NK cells were markedly reduced, whereas other populations, including γδ T cells, remained intact compared with PLZF+/+ BM mice (Supplementary Fig. 7B–E). Adoptive transfer of MAT-ILC1s isolated from CLP 6h mice into PLZF−/− BM mice (Supplementary Fig. 7F) resulted in a significant increase in PD-1 expression on γδ T cells, without altering their numbers (Supplementary Fig. 7G–K). These data corroborate the observed reduction in PD-1 expression on γδ T cells in the absence of ILC1s (Supplementary Fig. 6E, F), further providing in vivo evidence of the potential interaction between ILC1s and γδ T cells via the PD-1/PD-L1 pathway in the MAT.

Overall, these observations demonstrate that MAT-ILC1s increase CD127 and PD-L1 expression upon the induction of peritonitis and contribute to the resolution of excessive acute inflammation, at least in part by negatively regulating TNF production through γδ T cells.

Methods
Mice
All experiments were approved by, and followed the guidelines provided by, the Institutional Animal Care and Use Committee (IACUC) of the RIKEN Yokohama Branch (AEY2025-020(2)) and performed in accordance with Japanese law. Mice were euthanized via cervical dislocation by experienced personnel prior to tissue collection and analysis.
C57BL/6 mice were from CLEA (CLEA Japan, Inc.), and Ly5.1 mice were purchased from Sankyo Labo Service Corporation. PLZF−/− mice were kindly provided by Dr. Derek Sant′Angelo44, and Ncr1 green Cre mice were kindly provided by Dr. Christian A. J. Vosshenrich30. Tbx21 flox (#022741: B6.129-Tbx21tm2Srnr/J) mice were purchased from Jackson Laboratory. All experiments were performed on 10–25-week-old female and male mice. All mice were housed and maintained under SPF conditions at the RIKEN Yokohama animal facility with a 12h day/night cycle and normal chow diet. Littermates were co-housed, and Sham- and CLP-treated animals were housed separately.

Induction of peritonitis, parabiosis mice, and spleen transplantation
Peritonitis was induced using a cecal ligation and puncture method previously reported11,45. The cecum was surgically exposed from the peritoneal cavity and ligated using sterile nylon sutures (Akiyama-seisakusyo, USP: 5-0, JIS: 1) at a distance of one-third from the end of the cecum. Next, a 21-gauge needle was used to puncture the lower region of the ligated cecum. The cecum was returned to the peritoneal cavity, allowing leakage of its contents. The muscular layer and skin were then sutured using sterile nylon sutures (Natsume-seisakusho Co., Ltd, 11mm, No. 6-0) and clipped with a 9mm AUTOCLIP Applier (Becton Dickinson). This surgical procedure was executed under anesthesia and on a 40°C-warming plate (Natsume-seisakusho Co., Ltd). Only a sham laparotomy without ligation and puncture was performed in the control group. Saline was injected subcutaneously after the surgery.
Disease severity was assessed using a clinical scoring system based on a previous report46, with some modifications. Mice were evaluated in three categories: eye opening, behavior, and appearance. Each category was scored on a scale from 0 to 3, and the sum of these scores was defined as the severity score (maximum score = 9). Eye opening was evaluated as follows: 0 = eyes fully open; 1 = slightly closed; 2 = half closed; 3 = mostly or completely closed. Behavior was assessed based on the response to tail stimulation and spontaneous movement: 0 = brisk aversive response; 1 = responds to stimuli but reduced activity; 2 = delayed response, unable to walk more than two steps; 3 = shows minimal or no movement. Appearance was evaluated based on posture and responsiveness: 0 = normal posture and responsiveness; 1 = mildly hunched posture or slightly reduced responsiveness; 2 = clearly hunched posture with delayed or weak responsiveness; 3 = severely hunched posture and no observable response to external stimuli. All scoring was conducted under blinded conditions by observers independent of the CLP procedures.
For the analysis of parabiosis mice, female Ly5.1 and C57BL/6 mice were surgically connected using the previously reported method24 under anesthesia and on a 40°C warming plate. Briefly, the hair was shaved, and the skin was cut from the elbow to the knee for exposure. The elbow-to-elbow and knee-to-knee of each mouse were ligated with nylon sutures (Natsume-seisakusho Co., Ltd, No. 3-0), and the skin of each mouse was joined. After 30 days of surgical parabiosis, the CLP procedure was performed.
The spleen of the Ly5.1 mouse was harvested, and both ends were cut to obtain the middle region. The spleen of the C57BL/6 mouse was exposed under anesthesia, and the middle region of the spleen was carefully excised to avoid damaging the visible blood vessels. The middle region of the spleen from the Ly5.1 mouse was transplanted into the spleen of the C57BL/6 mouse from which the central portion had been excised. Each end of the spleen was surgically connected with nylon sutures. Mice were analyzed 4 days after surgery.

Cell isolation from the MAT, spleen, MLN, blood, and bone marrow
Single cells were isolated from the MAT according to a previously reported protocol with minor modifications47. Briefly, the small intestine (SI) containing the MAT was first collected from mice, and the MAT was then minced in 7 ml of 4% BSA in DMEM (Sigma Aldrich, Cat# D5796-500ML) in a 15 ml tube before the addition of 100 µl of 1.0 mg/mL Liberase DH (Roch, Cat# 5401054001) to digest the MAT. Tubes were shaken for 60 to 80 minutes at 37°C, 170 rpm by Stack Shake C (Waken Btech Co., Ltd.), and shaken vigorously by hand every 20 minutes during this enzyme digestion. After cell dissociation, isolated cells were collected by centrifugation and pellets, termed stem cell vascular fraction (SVF), were suspended in RPMI-1640 medium (Sigma Aldrich, Cat# R0883-500ML) containing 2% fetal bovine serum (FBS) after removal of red blood cells with RBC lysis buffer (BioLegend, Cat# 420302). Cells were passed through a 48 μm nylon filter to obtain a single cell suspension.
For the spleen and MLN isolation, each tissue was ground on a 100 μm cell strainer (Falcon) in RPMI-1640 medium, and red blood cells were removed with RBC lysis buffer. Cells were passed through a 48 μm nylon filter to obtain a single cell suspension.
For lymphocytes preparation from the blood, peripheral blood samples were treated with RBC lysis buffer to remove red blood cells. After washing with cold RPMI-1640 medium, the cells were filtered through a 48 μm nylon filter to obtain a single-cell suspension.
To obtain bone marrow cells, bones from the forelimb and hindlimb from PLZF+/+ or PLZF−/− mice were crushed in a mortar. After treatment with RBC lysis buffer, cells were resuspended in 2% RPMI, passed through a 48 μm nylon filter, and washed twice with cold PBS. 1~3×106 cells in PBS were adoptively transferred into Ly5.1 mice to generate chimera mice, and the MAT and spleen were analyzed after 2 months.

Adoptive cell transfer of spleen cells, bone marrow cells, or ILC1s
To transfer spleen-derived lineage-negative cells from healthy CD45.2 mice, the following biotinylated antibodies were used for negative selection by AutoMACS: TER119 (clone: TER119, Biolegend), CD3ε (clone: 145-2C11, BioLegend), TCRβ (clone: H57-597, BioLegend), TCRγδ (clone: GL3, BioLegend), CD19 (clone: 1D3, BD Pharmingen), F4/80 (clone: BM8, BioLegend). After negative selection, 1.0×107 CD45.2+ Lin− cells suspended in 200 µl PBS were intravenously transferred into the CD45.1 mice one day before CLP treatment. To evaluate spleen-to-MAT migration of transferred splenic ILC1s, the migration percentage was calculated as follows: [number of donor-derived ILC1s in the MAT of the recipient mouse] / [number of donor-derived ILC1s in the recipient MAT + number of donor-derived ILC1s in the recipient spleen] × 100.
To generate PLZF−/− or PLZF+/+ bone marrow mice, 12-week-old Ly5.1 mice were irradiated with 9.5 Gy at the RIKEN Yokohama RI facility. 1~3×106 bone marrow cells from the PLZF−/− or PLZF+/+ mice were injected i.v. into the irradiated Ly5.1 recipients and allowed to acclimate for at least 60 days before i.v. adaptive transfer of sorted CD49b− ILC1s (CD45.2+ CD3ε− TCRβ− TCRγδ− CD19− NK1.1+ NKp46+ CD49b− cells) from the MAT (2.5~3×103 cells). CLP was performed 12 hr after the transfer of CD49b− ILC1s.

Flow cytometric analysis and cell sorting
Single cell suspensions were stained with LIVE/DEAD fixable Aqua Dead Cell Stain (ThermoFisher Scientific) before blocking Fc receptors with the 2.4G2 mAb (BD Pharmingen) as previously described14. Cells were then stained with antibodies for surface antigens as follows: TCRβ (FITC or APC-Cy7 or BV605 or BUV737, clone: H57-597, BioLegend or eBioscience), TCRγ/δ (FITC or BV605, clone: GL3, BioLegend), CD3ε (FITC or APC or BV605 or BUV737, clone: 145-2C11, BioLegend or eBioscience), CD4 (APC-Cy7, clone: GK1.5, BioLegend), CD8α (FITC, clone: 53-6.7, BD Bioscience), CD19 (FITC or BV605, clone: 1D3 or 6D5, BD Pharmingen or BioLegend), CD27 (APC, clone: LG.3A10, BioLegend), CD45.1 (BV421 or BV785, clone: A20, BioLegend), CD45.2 (PerCp-Cy5.5, clone: 104, BioLegend), CD49a (APC, clone: HMα1, BioLegend), CD49b (PE, clone: DX5, eBioscience), CD127 (PE-Cy7, clone: A7R34, BioLegend), NKp46 (FITC or BV421, clone: 29A1.4, BioLegend), NK1.1 (APC-Cy7 or BV785, clone: PK136, BioLegend), PD-1 (APC, clone: 29F.1A12, BioLegend), PD-L1 (BV605, clone: 10F.9G2, BioLegend), Ly6C (BV421, clone: HK1.4, BioLegend), F4/80 (FITC, clone: BM8, BioLegend), CXCR3 (APC, clone: CXCR3-173, BioLegend), ST2 (APC, clone: DIH9, BioLegend).
For transcription factor staining, isolated cells were fixed and permeabilized with the Foxp3/Transcription Factor Buffer Set (ThermoFisher Scientific Cat# 00-5523-00) according to the manufacturer′s instructions after staining for surface antigens. Cells were then stained with intracellular antibodies: GATA3 (PE, clone: 16E10A23, BioLegend), RORγt (BV421, clone: Q31-378, BD Horizon), EOMES (Alexa488 or PE, clone: Dan11mag, eBioscience), T-bet (PE-Cy7, clone: 4B10, BioLegend), Foxp3 (APC, clone: FJK-16s, eBioscience), Ki-67 (PE, clone: 16A8, BioLegend).
For cytokine detection, the single cell suspension was stimulated with 50 ng/ml of phorbol myristate acetate (Sigma) and 2 µg/ml of ionomycin (Sigma) for 90 min at 37°C in the presence of GolgiPlug (BD Biosciences). Cells were stained with surface antibodies and then fixed with 4% paraformaldehyde or the Foxp3/Transcription Factor Buffer Set after two washes with PBS. Fluorochrome-conjugated intracellular antibodies IFN-γ (FITC or BV421, clone: XMG1.2, BioLegend), TNF-α (PE or APC, clone: MP6-XT22, BioLegend or eBioscience) or IL-17A (APC or PE-Cy7, clone: TC11-18H10.1, BioLegend) were diluted in 1x Perm buffer provided from the Foxp3/Transcription Factor Buffer Set and stained for 60 min at 4°C.
For identification of ILC subsets, NK cells were defined as CD45.2+ CD3ε− TCRβ− TCRγδ− CD19− RORγt− NK1.1+ EOMES+, ILC1s as CD45.2+ CD3ε− TCRβ− TCRγδ− CD19− RORγt− NK1.1+ EOMES−, ILC2s as CD45.2+ TCRβ− CD3ε− CD19− RORγt− Gata3+ ST2+, and ILC3s as CD45.2+ TCRβ− CD3ε− CD19− RORγt+. For lymphocyte analysis, cells were first strictly defined by forward scatter (FSC) and side scatter (SSC) parameters, followed by gating on live cells for each analysis.
All stained cells were analyzed or sorted on BD FACSAria III or BD LSRFortessa X-20 Cell analyzer, and the data obtained were analyzed using FlowJo v10.8.1 (BD Biosciences).
All FACS antibodies used in this study, including catalogue numbers and staining dilutions, are provided in Supplementary Table 1.

Cytokine and chemokine measurements in MAT and plasma
MAT was collected and crushed using the SK-miru (TOKKEN, Inc.) in liquid nitrogen after weight adjustment, and diluted RIPA buffer (Merck, Cat# 20-188) was used to lyse the crushed MAT. The tubes were then placed on ice for 3 h and mixed by vortexing every hour. After centrifugation at maximum speed, the resulting tissues were discarded, and the supernatant was transferred to new tubes; this step was repeated 3 times. After the last step, the supernatant was aliquoted and stored at −20°C until the analysis. Whole blood samples were collected from each mouse, and plasma was prepared by centrifugation. An ELISA assay was performed to evaluate IL-7 (R&D system, DY407), Lipocalin-2 (R&D system, MLCN20), IL-1β (BioLegend, 432604), and TNF-α (R&D system, MHSTA50). Cytometric Beads Array (BD Pharmingen) was used for IL-6 measurement, and Luminex assay systems (LXSAMSM-33, LXSAMSM-03, and LXSAMSM-01) were also performed for the comprehensive analysis of cytokines and chemokines in the MAT according to the manufacturer′s protocol. All samples were stored at −20°C until the analysis.

Administration of recombinant proteins, anti-CXCR3 antibody, anti-PD-1 antibody, and anti-TNF antibody
5 µg of recombinant IL-7 (BioLegend, Cat# 577804) in 200 µl PBS was administered i.p. 1 day before CLP and then again i.v. after CLP. Control mice were treated with PBS only at the same time points.
For in vivo antibody treatment, 200 µg of monoclonal anti-CXCR3 antibody (BioXcell, clone: CXCR3-173, Cat# BE0249), 250 µg of monoclonal anti-PD-1 antibody (BioLegend, clone: 29F.1A12, Cat# 135247), or 250 µg of monoclonal anti-TNFα antibody (BioXcell, clone: XT3.11, Cat# BE0058) in 200 µl PBS was administered intraperitoneally 3 days and 1 day prior to CLP, and intravenously immediately after CLP. Control mice were given the same volume of hamster IgG (BioXcell, Cat# BE0091), Rat IgG2a, k (BioLegend, Cat# 400565), or Rat IgG1 (BioXcell, Cat# BE0088).

Gene analysis by CITE-seq
For CITE seq library preparation, SVF single cells isolated from the MAT of each mouse group were stained with TotalSeq B antibodies (BioLegend) after blocking with Fc receptor (2.4G2) as follows: I-A/I-E (clone: M5/114.15.2), CD19 (clone: 6D5), CD27 (clone: LG.3A10), CD45.2 (clone: 104), CD49a (clone: HMa1), CD127 (clone: A7R34), FcεR1 (clone: 1-Mar), KLRG1 (clone: 2F1/KLRG1), Ly6C (clone: HK1.4), NK1.1 (clone: PK136), TCRβ (clone: H57-597), PD-1 (clone: RMP1-30), PD-L1 (clone: MIH6), Rat IgG2ak (clone: 400581), Rat IgG2bk (clone: RTK4530). After staining, the lymphocyte fraction, gated on SSC vs FSC, excluding the dead cells stained with PI, was sorted before passing through the 10X chromium controller to generate the droplets.
The library was generated according to the protocol of Chromium Next Gem Single Cell 3ʹ Reagent Kits v3.1. Each library was sequenced using Hiseq X (Illumina). All TotalSeq B antibodies used in this study, including catalogue numbers and staining dilutions, are provided in Supplementary Table 2.

Clustering and gene expression analysis with Seurat and CellphoneDB
Demultiplexing and UMI counting of each FASTA file was performed using the Cell Ranger pipeline (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/latest/using/tutorials) and the files 'barcodes.tsv, features.tsv and matrix.mtx were generated using the mouse genome reference mm10. These files were imported into RStudio, and the Seurat objects were created using the R package Seurat v4.0 and analyzed as described below using the Seurat tutorial (https://satijalab.org/seurat/)48. Cells containing more than 10% of mitochondrial genes were removed as dead cells. To visualize and identify the clusters, dimensional reduction was performed using UMAP after scaling the data, and each cluster was characterized based on cluster-specific gene and protein expression. ILC1/NK clusters were extracted from all clusters based on protein expression of NK1.1 > 0.5, TCRβ < 0.5, and CD19 < 0.5, and gene expression Cd3e < 0.5, then re-clustered. After sub-clustering, both Seurat object sham control and CLP 6h were integrated using canonical correlation analysis (CCA).
Gene expression analysis was performed according to the Seurat protocol using the “FindMakers” function, with or without RECODE reprocessing (https://yusukeimoto.github.io/images/RECODE_R_Tutorials/Run_RECODE_on_R_tutorial.html)49. Gene and protein expression information was visualized in volcanoplots and violin plots.
For cell-cell interaction analysis, CellPhoneDB v2.0 was used for ligand-receptor pairs analysis28. To understand the interaction of T cells and ILC1 at CLP 6h and above, ILC1/NK and T cell clusters were extracted from all Seurat clusters of the CLP 6h dataset as ILC1/NK/T cell-Seurat objects. Then, count data and metadata were obtained from the ILC1/NK/T cell-Seurat object and the ensemble symbol of mouse was changed to that of human, because CellPhoneDB only accepts the human symbol for analysis. Using the count and metadata files, ligand-receptor pairs and cluster pairs that interact with each other were identified and visualized as heatmaps and bubble plots, using the Python 3 pipeline, following the CellPhoneDB tutorial.

RNA extraction and quantitative PCR analysis
5 mm of the MAT was frozen and crushed using the SK-miru (Tokken, Inc.) in liquid nitrogen after washing with PBS. The crushed tissues were then lysed in RLT buffer (QIAGEN, Cat# 74106) containing 2-mercaptoethanol (Nacalai Tesque, Cat# 21438-82). The RNeasy Mini Kit (QIAGEN, Cat# 74106) was used for total RNA extraction according to the manufacturer′s instructions. Isolated RNAs were then converted to cDNAs by RiverTra Ace (TOYOBO, Cat# TRF-101) using random primers (TOYOBO, Cat# FSK-301). Quantitative PCR was performed using the SYBR Premix Ex Taq (Takara, Cat# RR820L) on a LightCycler 480 (Roche) or Thermal Cycler Dice TP800 (Takara Bio Inc.) with the following primers. Hprt50: Fw, 5′-CCTAAGATGAGCGCAAGTTGAA-3′, Rv, 5′-CCACAGGACTAGAACACCTGCTAA-3′; Il6: Fw, 5′-ATGGATGCTACCAAACTGGAT-3′, Rv, 5′-TGAAGGACTCTGGCTTTGTCT-3′; Il1b51: Fw, 5′-CGACAAAATACCTGTGGCCT-3′, Rv, 5′-TTCTTTGGGTATTGCTTGGG-3′; Lep: Fw, 5′-GCAAGAAGAAGAAGATCCCAGG-3′, Rv, 5′-CAGATAGGACCAAAGCCACAG-3′; Lcn2: Fw, 5′-TGGCCACTTGCACATTGTAG-3′, Rv, 5′-ATGTCACCTCCATCCTGGTC-3′.

Statistical analysis
Statistical analysis and visualization of results were conducted using Prism v.9 or R v4.2.1. Biological represented data are presented as mean ± standard error of the mean (SEM). Outliers were identified and excluded using Tukey′s method implemented in GraphPad Prism. Data were tested for normality using the Shapiro-Wilk test prior to statistical analysis. For normally distributed data, statistically significant differences between two groups were detected by two-tailed Student′s t test, among multiple groups using one-way ANOVA with Tuky′s-test. For non-parametric data, the Mann–Whitney U test or Kruskal–Wallis test followed by Dunn′s multiple comparison test was used. Differences between groups classified by two independent factors were detected by two-way ANOVA with Sidak′s test. For the gene expression analysis in the CITE-seq data, MAST was selected in the Seurat command ‘FindMakers’ to detect the significance52.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript entitled, “PD-L1 expressing CD127+ ILC1s inhibit PD-1+ γδ T cells in the mesenteric adipose tissue to alleviate murine peritonitis” reports the role of crosstalk between mesenteric adipose tissue (MAT)-CD127+ILC1s and γδ T cells through the PD-1/PD-L1 pathway in controlling CLP-induced acute peritonitis by suppressing excessive inflammation. In this article, the authors showed that ILC1 expressing high levels of IL-7Ra (CD127) are increased during acute peritonitis, and they suppress the TNFa+ gamma delta T cell function via direct contact with the cells via PD-L1 and PD-1 interaction. The authors showed that those ILC1s originated from the spleen, and were recruited to mesenteric adipose tissue via CXCR3 – CXCL10 axis. The authors performed various robust experiments and tried to discover the systemic and cellular mechanism for regulating inflammatory gamma delta T cells via ILC1s. While most of the conclusions are well supported by convincing data, additional experiments and appropriate control should be performed and included to further strengthen the manuscript.\n\nMajor comments:\n1. The authors utilized CLP as an inducer of peritonitis. This model naturally progresses to sepsis, leading to mortality in the mice. Depending on the severity of CLP, it appears to influence the degree of temperature drop and the time required for recovery. The authors specifically focus on peritonitis, as mentioned in the title of the paper. According to the Methods section, the authors performed a 0.5 cm cecal exposure, which corresponds to a moderate CLP induction. However, the more significant temperature changes seem to occur at later time points, such as 8 and 12 hours, rather than at 6 hours. Therefore, further explanation is needed as to why the authors chose to focus on the 6-hour time point.\n2. Moreover, the differences in survival observed in the later stages of the study are ultimately related to the effects of sepsis. If the authors aim to focus on peritonitis, they should demonstrate changes in phenotypes other than temperature to justify their discussion of the immune response to peritonitis.\n3. The authors claimed that mesenteric adipose tissue (MAT) ILC1 is associated with acute peritonitis (line 81-83). As a reason for the claim, the authors showed the increased cell number in ILC1, while the number of other ILCs or NK cells did not increase. However, the absolute cell number of ILC1 is lower than NK cells or ILC2. Furthermore, the authors did not show the number of peritoneal myeloid cells, such as macrophages and neutrophils, which are abundant in peritoneal cavity and participate in inflammatory pathways such as acute peritonitis. Understanding the relative abundance of ILCs among other immune cells could provide important context for their role in the immune response. The authors need to sufficiently explain why they focus on ILCs over the many other types of infiltrating immune cells. There are some models to specifically deplete ILCs while sustaining T cell functionality (Rafei-Shamsabadi, D, A. Lack of Type 2 Innate Lymphoid Cells Promotes a Type I-Driven Enhanced Immune Response in Contact Hypersensitivity. J Invest Dermatol (2018)). If the authors have performed such a specific ILC depletion, then the importance of ILCs will be highlighted.\n4. In Figure 2D and Figure 2E, the authors claimed cluster 1 cells are a mixed population of NK cells and ILC1. However, in the violin plot, cluster1 expressed the highest level of T-bet (Tbx21) and IFN-gamma (Ifng). Therefore, rather than a mere mixture of cells, the cluster is a specific cluster with specific gene expression. Therefore, the authors at least show the feature genes to see the signatures of each clusters, not merely annotating them as mixture of cells.\n5. In both the Figure 2E and Extended Data Figure 2A legends, it is clear that the same dataset was used. The CITE-seq results refer to the ILC1/NK population. However, why is there a discrepancy between the expression patterns of CD127 and IL7r? These are aliases for the same gene. It is necessary to verify whether the authors have confused the results obtained from different datasets.\n6. In Figure 2F, the authors gated CD127- ILC1 and NK cells together to assess IFN-γ expression. However, based on Figure E and previous studies, there are likely differences in the IFN-γ expression potential between these two cell types. For more accurate analysis, it would be better to first distinguish ILC1 and NK cells based on EOMES expression. Following this, the ILC1 population could be further subdivided according to CD127 expression levels for a more precise assessment of IFN-γ production in each group.\n7. I wonder why there is no analysis of CD127+ ILC1 in the sham group in Figure 2F. It would be interesting to know if CD127+ ILC1 show not only numerical differences in the CLP group but also changes in functional characteristics such as IFN-γ expression, or if CD127+ ILC1 inherently produce low levels of IFN-γ, regardless of CLP. Additionally, investigating the differences in cell characteristics between these groups could be further explored by performing a more detailed analysis of the single cell analysis data from Figure 2D, separating the Sham and CLP groups.\n8. In figure 2C, the authors state that after 6 hours of CLP, number of total ILC1 increase 2-fold (500 to 1000). In figure 3F and 3J, after parabiosis and spleen transplant experiments, the percent of ILC1 counterpart that the authors claim to derive from the spleen out of whole ILC1 increase from 4 to 10 percent for parabiosis experiments and 1 to 3 percent for spleen transplant experiments. Which means that the spleen derived ILC1 cannot explain the 2-fold increase in total ILC1 in MAT after CLP. Therefore, while it is reasonable to assert that some ILC1 migrate from the spleen to the MAT, authors need to conduct additional experiment for explaining the 2-fold increase in figure 2C. Moreover, since spleen-derived ILC1s constitute such a small population of the whole ILC1 population in the MAT in both sham and CLP condition, it is necessary to prove that these cells are a critical contributor to the phenotypes observed.\n9. If ILC1 are derived from spleen, authors should verify increased ILC1 circulation in blood with markers including CD127, CXCR3 and Ly6C.\n10. FACS data in figure 2B shows that CD127+ ILC1 constitute up to 60% of the whole ILC1 population in MAT 6h after CLP. However, cluster 0 in the UMAP plot in figure 2D, which the authors claim to be the MAT-CD127+ ILC1s does not seem to occupy 60% of the whole ILC1/NK group, and indeed it seems to be such a small population in the UMAP plot. Authors should clarify the discrepancy between FACS and CITE-seq data.\n11. While Ly6C, Cxcr3, and PDL1 are emphasized as key molecules in the manuscript, the authors do not present transcriptomic data for these markers. Providing RNA-level expression data for these molecules would not only complement the current findings but also offer a more comprehensive understanding of their biological significance. Furthermore, since the earlier figures consistently distinguish between CD127+ ILC1 and CD127- ILC1 populations, it would be more scientifically rigorous to compare the expression levels of these molecules within this established framework. This approach would strengthen the clarity and validity of the authors' conclusions.\n12. The authors demonstrated the role of the CXCR10-CXCR3 axis in ILC1 migration. While CXCL10 protein expression was assessed in the MAT, and CXCR3 expression on ILC1s was measured in the spleen, it has not been evaluated in the MAT. Therefore, it is important to confirm the expression of CXCR3 on ILC1s within the MAT.\n13. In lines 202-204, you said CD127+ ILC1s “drive TNF-α production” in γδ T cells through the PD-1/PD-L1 pathway. This sentence contradicts your data and previous words in this paper.\n14. In the Extended data Figure 5 experiment, is there any data on how many adoptively transferred CD45.2 MAT-ILC1s were in the host MAT at CLP 6h?\n15. In the Extended data Figure 5 experiment, you used the bone marrow transfer to make an ILC1-depleted mouse and transferred ILC1 to see the effect of the existence of ILC1. Why did you transfer ILC1 from MAT of the CLP-induced mice? Your previous study shows that the splenic ILC1s are migrated to MAT when CLP is induced. Transferring splenic ILC1s from healthy mice is better to show your hypothesis. Or transplant a PLZF-/- spleen or PLZF+/+ spleen from healthy mice to PLZF-/- bone marrow transplanted mice to see the exact mechanism of the splenic ILC1s.\n16. In Figure 6, TNF-α+ γδ T cells represent only a small subset of the total cells. It raises the question of whether γδ T cells are the primary producers of TNF-α in response to CLP when ILC1s are absent. Also, to determine if TNF-α-producing γδ T cells regulated by ILC1s are the main contributors to preventing excessive inflammatory responses, additional experiments such as γδ T cell depletion, blocking, or TNF inhibitors treatment would be necessary. These experiments would help clarify whether γδ T cells regulated by ILC1s play a central role in controlling inflammation in this context.\n\nMinor comments:\n1. In the supplementary figure 2A, the authors wrote the protein level on the violin plot, while the violin plots show mRNA expression value.\n2. Given the overall flow of the paper, ILC1 is the most critical population. Why are there no marker genes distinguishing the clusters in Figures 2D and 2E?\n3. In line 130, authors referenced reports on the role of IL-7 in downregulating CD127 expression, and states that such results are consistent with their findings. Is the any reason why authors chose the reference on T cells?\n4. Figure 3M and 3N should include data after CLP.\n5. Authors should show proportion difference between sham and CLP 6h condition of the UMAP cluster in figure 2D.\n6. It would be helpful to label \"Cont\" and \"a-PD-1 Ab\" in Figures 5F and 5G respectively.\n7. It would be better to consistently use either \"CD127+ ILC1\" and \"CD127- ILC1\" with spaces or \"CD127+ILC1\" and \"CD127-ILC1\" without spaces throughout the manuscript, as the current version inconsistently mixes both formats.\n8. In Extended Data Figure 4, there is no gating strategy provided for CD4, CD8, and γδ T cells. When presenting the PD-1 levels, it would be more appropriate to display these marker genes on the y-axis. Alternatively, it would be helpful to include the pre-gating strategy for these populations.\n9. Extended data Figure 4. C and D are not mentioned. It's better to explain the data in the main text or remove it.\n10. At line 202, it's better to unify the terminology: Extended Fig. 4B to Extended data Fig. 4B.\n11. In line 218, the nomenclature “PLZF-BM chimera mice” appeared, but you transplanted bone marrow from both PLZF-/- and PLZF+/+ mice. It's better to clarify what the PLZF-BM mice are.\n12. In the Extended data Figure 5A, the scheme said that MAT-ILC1 or PBS were injected into both the PLZF-/- chimera and the PLZF+/+ chimera. Is it true that you used the four-mouse condition?: PLZF-/- chimera + MAT-ILC1, PLZF-/- chimera + PBS, PLZF+/+ chimera + MAT-ILC1, and PLZF+/+ chimera + PBS. I'm very confused with the experimental scheme even after reading the figure legend. The presentation of the scheme should be improved, and the data below should be clearly stated, comparing which mice and which mice.\n13. Do PD-1+ γδ T cells or TNF-α producing γδ T cells express RORγt or T-bet?\n14. Line 358: it should be \"adoptive cell transfer\" rather than \"adaptive cell transfer.", "reviewer_2": "This manuscript examines the role of CD127+ ILC1s in the mesenteric adipose tissue in a low mortality model of cecal ligation and puncture\n\nMajor comments:\n1) Globally, the manuscript often conflates association with mechanistic causation. There are a number of times when the authors find the two phenomena are associated, but this does not mean that one causes the other.\n2) The authors examine a few parameters in figure 1 at 6 hours and 24 hours and find that differences are greater at 6 hours than 24 hours and conclude that “the strongest inflammatory condition occurs at around 6 hours.” This conclusion cannot be drawn. All they can conclude is that inflammation is stronger at 6 hours than 24 hours as inflammation might be greater at 1 or 3 or 8 or 12 hours than 6 hours and the authors did not examine for this. The same is true when the authors state that bacterial invasion was maximally detected at 6 hours after CLP when they only examined 6 and 24 hours.\n3) The results state that IL-b is decreased 24 hours after CLP in figure 1D. This is not consistent with what is in the figure.\n4) Some of the n’s in figures are quite low. For instance, figure 1E appears to be n=3. It is difficult to conclude anything meaningful from such a low sample size.\n5) Quantification should be shown for figure 1G.\n6) ILC-1 number are not different between 6 and 24 hours and are not different between sham and 24 hours. It may or may not be that the differences seen between sham and 6 hours are meaningful based upon this.\n7) The conclusion on line 131 that the results “suggest that CD127 expression ILC1s was altered by the reduction of IL-7 in the MAT during acute inflammation, leading to an increase in CD127+ ILC1s at CLP 6h” is not supported by the data presented. As per point 1, correlation is not the same as causation.\n8) The parabiosis experiments are poorly described and difficult to understand.\n9) A decrease in splenic Ly6C+CD127- cells could potentially indicate migration but it could also indicate that these cells die – a possibility that is not considered in the manuscript.\n10) The anti-CXCR3 experiments do not look at MAT. Therefore it is difficult to see how conclusions can be drawn regarding the MAT.\n11) The data in figure 4D and E is also associative rather than proving causation.\n12) Similarly, the data in Fig. 5F and G are also associative. While one certainly cannot refuse the authors statement in the results that this indicates a “possibility” of a mechanistic relationship, that is more speculative for the discussion.\n13) The ILC-1 deficient mice appear to be globally deficient as opposed to specifically in the MAT.\n14) While the authors acknowledge that figures 6C and D only show a “potential interaction” between ILC1 and gamma/delta T cells via the PD-PDL1 pathway in the MAT, there is also an association as opposed to a clear link.\n15) Were mice given pain medicine? If so, this needs to be stated. If not, the reason for withholding them needs to be clearly stated.\n16) Were data tested for a normal distribution? This is required prior to using a t test – otherwise a non-parametric test should be used. If so, this should be included in the statistics section. Otherwise, this needs to be checked and the statistics redone (some of the groups are too small to have a normal distribution).\n\nMinor comments:\n1) The first line of the introduction states that “peritonitis is a critical illness.” Peritonitis simply means inflammation of the peritoneum. Peritonitis could be associated with critical illness but more often than not is not as most patients with acute abdomens do not end up in the ICU.\n2) What was the sex of mice used? This is not stated.\n3) 10-25 weeks is a large span of mouse age ranging from young to middle aged. Why was such a large span of ages used and were mice age matched in each experiment?", "reviewer_3": "In the present manuscript Nagata et al investigated the role of ILC1s during peritonitis, by using a model of cecal ligation and puncture (CLP). The authors show that upon inflammation the numbers of ILC1s transiently increase in the mesenteric adipose tissue (MAT), alongside their expression of CD127. These cells possess a unique phenotype producing less IFNg than their CD127- counterparts and expressing high levels of PD-L1, suggestive of a regulatory role. Indeed the authors show that genetic ablation of ILC1s induces increased inflammation, as evidenced by more TNF production by gd T cells and decreased body temperature, ultimately decreasing survival of the animals. Interestingly, the authors suggest that these \"regulatory\" ILC1s migrate from the spleen to the MAT in a CXCR3-dependent manner. The findings presented here are novel and part of them are supported by very elegant approaches. In my opinion, however, this manuscript would benefit from additional experiments to strengthen the authors' claims, as delineated below.\n\nMajor points:\n- Even though Nagata et al used very interesting approaches to pinpoint a role for migration in the ILC1 response during CLP (such as spleen transplants and parabiosis), I think some key points need to be addressed. First, in Figure 1h, we observe that the numbers of ILC1 double at 6h post CLP, however, in both the parabiosis and transplantation experiments, the frequency of ILC1s coming from circulation is less than 10% (9% and 5% on average, respectively). Have the authors checked for local proliferation? Also, could these ILC1s coming from other tissues such as the liver and gut? Upon CXCR3 blockade the authors observe an enrichment in ILC1s in the Spleen (suggesting that the cells are trapped there); but have the authors checked to see if CXCR3 blockade prevents the increase in ILC1s in the MAT? Finally, I understand the difficulty of underlying the spleen transplant experiment, but the n for that experiment seems quite low (so much so, that the difference in CD45.1+ ILC1s is not even significant) and I cannot find anywhere if/how many times that experiment has been repeated. As this supports a big conclusion of the paper, the authors should repeat this experiment to increase the n;\n- Still regarding the migration of ILC1s to the MAT, have the authors checked if blockade of CXCR3 induces an increase in cytokine production by gd T cells? What about the inflammatory response and survival of these mice?\n- Another important conclusion of the paper is that ILC1 suppression of gd-derived TNF restricts inflammation during peritonitis. Whereas by the CITE-Seq data it looks only gd T cells produce TNF (Extended Data Fig 4) the intracellular cytokine levels of TNF in gds seem very low (Fig 5g) and even the total protein levels in the MAT is the lowest when compared to all the other inflammatory markers (Fig 1e). This raises the question if suppression of gd-derived TNF mediates the regulatory role of ILC1s. The authors should formally address the role of TNF in the survival and regulation of body temperature of CLP mice, for instance by blocking TNF in the Ncr1Cre X Tbx21Flox mice;\n- Is the acquisition of CD127 (and the associated regulatory phenotype, i.e. low IFNg production and PD-L1 expression) dependent only on the low IL-7 levels? If so, blocking IL-7 in naïve mice, or other inflammatory conditions that decrease IL-7 levels would also lead to the appearance of these regulatory ILC1s. Finally, do the authors have a hypothesis for how low levels of IL-7 might suppress the IFNg and increase PD-L1 expression?\n\nMinor points:\n- Bone marrow chimeras have a severe deficiency in the population of IL-17-producing gd T cells (Haas, Immunity, 2012) - which are the subset known to reside in adipose tissue. When working with populations that are not radio-resistant, a way to overcome this problem is by injecting neonatal thymocytes along adult bone marrow (Papotto, EMBO Reports, 2017). Have the authors checked that the gd population in the MAT is comparable to that from non-bone marrow chimeras? I.e., are they still able to produce IL-17 and TNF?\n- How do the authors explain that PD-L1 from ILC1s induce PD1 expression in gd T cells? Could the first be secreting another cytokine/factor that increases PD1 expression instead?\n- Do splenic CD127+ ILC1s also produce low levels of IFNg and express PD-L1?\n- What happens to ILC1s to reach normal numbers at 24h post CLP? Do they die or do they migrate somewhere else? Have the authors performed annexing staining or checked for CD45.1+ cells in other organs from the parabiotic/transplanted mice, for instance?\n- In the final point of their discussion the authors suggest that giving recombinant IL-7 could be beneficial to patients with sepsis. However, wouldn't this go against what the data shows? Reduced IL-7 induces \"regulatory\" ILC1s that curb inflammation during sepsis?", "reviewer_4": "This study by Nagata et al highlights the migration of ILC1s from the spleen to MAT and their interaction modulating γδ T cells via PD-1/PD-L1 during acute peritonitis. The findings contribute to further understanding of migratory behaviours in ILCs, particularly ILC1’s, and their interaction with other immune cells namely gdT cells. Here, they identified the PD-1/PD-L1 ligand-interaction as the mechanism for ILC1’s controlling gdT cell-mediated secretion of TNF and subsequent inflammation.\nThe mouse model Ncr/Tbx21 is compelling in demonstrating the role of ILC1 in early timepoints in this peritonitis model and represent a useful mouse model for the field. Parabiosis and splenic surgery are methodologically convincing to evidence of ILC1’s migration, further adding to the field’s understanding of circulating vs tissue resident ILCs.\nWhile this study adds to immune cell function within AT, this reviewer suggests the following to better contextualise and support the study’s conclusions.\nIn determining the mechanistic crosstalk and what CD127+ PD-L1+ ILC1’s are acting on, the authors primarily pursued PD1+ gdT cells and their increased TNF production. Could other cells play a (bigger) role: There is a risk of over-simplification on immune cell crosstalk here as the authors only showed bulk CD4 and CD8 T cells not expressing PD1. Is there more data or discussion from gdT cell deficient models? More adequate analysis that other immune or T/innate-like T cell populations are not directly affected by migratory ILC1’s or express PD1 will be more convincing, using analysis on the Ncr/Tbx21 mice, or at the very least discussed.\nCould TNF be a or one of many bystander effects of gdT cell activation? There is a risk of disproportionate focus on TNF from gdT cells driving this acute pathology, as they constitute a relatively minor population of ILC1’s/lymphocytes (eg <0.4% in Fig 5). Is this cytokine from gdT more critical and specific to MAT immune responses during CLP? What’s the relative contribution of total TNF increase by gdT cells against other cells? On the other hand, the critical role of TNF seems to be downplayed in significance from the start (in Fig 1) prior to pursuing the TNF-producing gdT cells. Are there further evidence or discussion on functional contribution of TNF in TNF deficient or neutralisation? Furthermore, data on longitudinal tracking of gdT cells and whether their TNF/other cytokine production significantly change towards resolution or progression across timeline post CLP could be informative.\nImportantly, details on number of mice and experiments are lacking from Fig 3 onwards across manuscript and figure legends thus it is difficult to ascertain the data reproducibility and rigor.\n\nMinor comments:\n• It will be helpful to ensure consistencies of figure details, there are clear labels for some but not others. Eg, Fig 2D, label the cells associated to the clusters and corresponding colours. Fig 3 flow cytometry plots, pre gated on ILC or ILC1? PD-L1+ ILC1’s for Fig 4E. For Fig 5B, clearer font sizes. For Fig 6G, just pre-gated on gdT cells?\n• Were the effects on body temp measurement post CLP in mice receiving anti PD-1 treatment in Figure 5?\n• Are these MAT PD1+ gdT cells the Vg6 subset (Edwards et al JEM 2023),and are the implicated gdT cells a specific subset that were already in the AT? As an aside, some gdT cells can express PLZF.\n• Please check for necessary references to support statements across the manuscript, eg lines 261-268.\n\nEditorial items:\nConsistency and accuracy in cytokines:\n• The official name for TNF has been just TNF, without the \"alpha\" suffix.\n• Figure 2 Legend: IFN-restricted. Important to stipulate IFN-g. Check manuscript for consistency and accuracy.\n• Reword to adoptive and not ‘adaptive’ transfer."}, "author_response": "Point-by-point responses to the reviewers’ comments\nWe thank the reviewers for their careful reading of the manuscript and their encouraging\ncomments and suggestions for improvements. Guided by these suggestions, we have prepared a\nrevised version of the manuscript (changes are indicated by red font), which includes additional\nexperimental data as requested. We also made minor modifications to the English throughout the\nmanuscript, but these did not change the content or meaning of the text, and therefore we did not\nchange these parts to red font. A point-by-point response to all comments made by the reviewers\nis found below. This section begins with the reviewer’s comment, followed by our response. We\nhave also attached Appendix figures 1 to 4 at the end of this document as additional information\nonly for the reviewers.\nReviewer #1 (Remarks to the Author):\nThe manuscript entitled, “PD-L1 expressing CD127+ ILC1s inhibit PD-1+ γδ T cells in the\nmesenteric adipose tissue to alleviate murine peritonitis” reports the role of crosstalk between\nmesenteric adipose tissue (MAT)-CD127+ILC1s and γδ T cells through the PD-1/PD-L1 pathway\nin controlling CLP-induced acute peritonitis by suppressing excessive inflammation. In this\narticle, the authors showed that ILC1 expressing high levels of IL-7Ra (CD127) are increased\nduring acute peritonitis, and they suppress the TNFa+ gamma delta T cell function via direct\ncontact with the cells via PD-L1 and PD-1 interaction. The authors showed that those ILC1s\noriginated from the spleen, and were recruited to mesenteric adipose tissue via CXCR3 – CXCL10\naxis. The authors performed various robust experiments and tried to discover the systemic and\ncellular mechanism for regulating inflammatory gamma delta T cells via ILC1s. While most of\nthe conclusions are well supported by convincing data, additional experiments and appropriate\ncontrol should be performed and included to further strengthen the manuscript.\nWe thank the reviewer for the critical comments and suggestions on our manuscript.\nMajor comments:\n1. The authors utilized CLP as an inducer of peritonitis. This model naturally progresses to sepsis,\nleading to mortality in the mice. Depending on the severity of CLP, it appears to influence the\ndegree of temperature drop and the time required for recovery. The authors specifically focus on\nperitonitis, as mentioned in the title of the paper. According to the Methods section, the authors\nperformed a 0.5 cm cecal exposure, which corresponds to a moderate CLP induction. However,\nthe more significant temperature changes seem to occur at later time points, such as 8 and 12\nhours, rather than at 6 hours. Therefore, further explanation is needed as to why the authors\n1\nchose to focus on the 6-hour time point.\nAs suggested by the reviewer, we measured body temperature at 3, 6, 9, 12, and 24 hours\nfollowing CLP. Consistent with our initial findings, we observed that the most substantial\ndecrease was detected at 6 hours post-CLP (see revised Supplementary Fig. 1A). These data\nindicate that 6 hours post-CLP represent the peak of disease severity, followed by a gradual\nrecovery.\n2. Moreover, the differences in survival observed in the later stages of the study are ultimately\nrelated to the effects of sepsis. If the authors aim to focus on peritonitis, they should demonstrate\nchanges in phenotypes other than temperature to justify their discussion of the immune response\nto peritonitis.\nTo further clarify the phenotypic changes induced by CLP, we evaluated clinical scores with\nparticular focus on body temperature and animal behavior. The scoring criteria are described in\nthe Methods section of the revised manuscript. Consistent with the finding that 6 hr post-CLP\nrepresents the most severe time point with the greatest drop in body temperature (see revised\nSupplementary Fig. 1A), clinical scores also peaked at this time point and gradually declined by\n24 hr post-CLP (revised Supplementary Fig. 1B). Supporting this observation, IL-6 levels in\nplasma exhibited a similar trend, with a peak at 6 hr followed by a decrease at 24 hr (revised\nSupplementary Fig. 1C). These results collectively indicate that acute inflammation was strongly\ninduced at 6 hr post-CLP and was substantially recovered by 24 hr.\n3. The authors claimed that mesenteric adipose tissue (MAT) ILC1 is associated with acute\nperitonitis (line 81-83). As a reason for the claim, the authors showed the increased cell number\nin ILC1, while the number of other ILCs or NK cells did not increase. However, the absolute cell\nnumber of ILC1 is lower than NK cells or ILC2. Furthermore, the authors did not show the\nnumber of peritoneal myeloid cells, such as macrophages and neutrophils, which are abundant\nin peritoneal cavity and participate in inflammatory pathways such as acute peritonitis.\nUnderstanding the relative abundance of ILCs among other immune cells could provide\nimportant context for their role in the immune response. The authors need to sufficiently explain\nwhy they focus on ILCs over the many other types of infiltrating immune cells. There are some\nmodels to specifically deplete ILCs while sustaining T cell functionality (Rafei-Shamsabadi, D, A.\nLack of Type 2 Innate Lymphoid Cells Promotes a Type I-Driven Enhanced Immune Response in\nContact Hypersensitivity. J Invest Dermatol (2018)). If the authors have performed such a specific\nILC depletion, then the importance of ILCs will be highlighted.\nneutrophils in acute peritonitis have been extensively studied. However, the role of ILCs in acute\ninflammation remains largely unexplored, despite the widely recognized significance of ILC1s in\nvarious other pathological conditions. To date, no detailed studies have specifically addressed the\ninvolvement of ILCs in acute peritonitis, highlighting the need to investigate their potential roles\nin this context. Supporting this, our data demonstrate that disease severity was exacerbated in\nILC1 KO mice following CLP, indicating a critical role of ILC1s (see original manuscript, Figure\n6A-K).\nAlthough ILC1s are less abundant than NK cells or ILC2s in the MAT, their functional\nimpact on disease progression appears to be disproportionate to their cell numbers. In fact, the\nnumber of NK cells did not show significant changes during peritonitis (Figure 1G in the original\nmanuscript). However, the expression level of granzyme B in NK cells was increased at 24 hr\nafter CLP (revised Supplementary Fig. 1F). This suggests that NK cells may contribute to the\nhomeostatic response during the resolution phase of inflammation. Similarly, ILC2 numbers also\nchanged at CLP 24hr, indicating that they may participate in the immune response during the\nrecovery phase.\nRegarding peritoneal granulocytes and monocytes, neutrophils and F4/80low Ly6C⁺\nmonocyte-like cells increased in the MAT at 6 hr after CLP and decreased by 24 hr (see Appendix\nfig. 1A and B, attached at the end of this document). By contrast, these changes were not observed\nin the peritoneal cavity (Appendix figure 1C), highlighting the importance of the MAT as a first\nline of defense during inflammation following intestinal perforation. Meanwhile, F4/80+ Ly6Clow\nmacrophages, known to contribute to tissue repair and the maintenance of homeostasis, were\nsignificantly increased at 24 hr after CLP in both the MAT and the peritoneal cavity (Appendix\nfigure 1, B and C). These changes in myeloid cell populations mirrored the progression and\nresolution phases of inflammation in CLP mice and are consistent with typical myeloid cell-\nmediated responses during acute inflammation. These points have been addressed and described\nin the revised manuscript (Discussion section, page 15, lines 322-324)\n4. In Figure 2D and Figure 2E, the authors claimed cluster 1 cells are a mixed population of NK\ncells and ILC1. However, in the violin plot, cluster1 expressed the highest level of T-bet (Tbx21)\nand IFN-gamma (Ifng). Therefore, rather than a mere mixture of cells, the cluster is a specific\ncluster with specific gene expression. Therefore, the authors at least show the feature genes to\nsee the signatures of each clusters, not merely annotating them as mixture of cells.\nIn the original analysis, NK cells and ILC1s were not separated, as it was difficult to clearly\n3\ndistinguish these populations based on Eomes and Il7r gene expression profiles at the single-cell\nRNAseq level. Based on the referee’s comments, we re-analyzed our dataset using RECODE, a\nmethod that applies noise reduction based on high-dimensional statistical modeling. This\napproach enabled us to obtain clearer gene expression signatures for distinguishing the previously\nmixed populations. By applying RECODE, the cluster 1 gene expression profile was consistent\nwith CD127― ILC1s. In contrast, another cluster that expressed CD127 was identified as CD127+\nILC1s (revised Figure 2, D and E, and revised Supplementary Fig. 2B). Consistent with these\nclassifications, each cluster displayed distinct gene expression patterns, such as RAR-related\norphan receptor alpha (Rora) and Nr3c1 (encoding the glucocorticoid receptor), as shown in the\nfeature gene heatmap. This point has now been added to the revised manuscript (Result section,\nlines 106-114 on pages 6-7; Discussion section, lines 294-321 on pages 14-15).\n5. In both the Figure 2E and Extended Data Figure 2A legends, it is clear that the same dataset\nwas used. The CITE-seq results refer to the ILC1/NK population. However, why is there a\ndiscrepancy between the expression patterns of CD127 and IL7r? These are aliases for the same\ngene. It is necessary to verify whether the authors have confused the results obtained from\ndifferent datasets.\nAs mentioned above, the resolution of the original scRNA-seq dataset was insufficient to clearly\ndistinguish the mixed NK/ILC1 population, particularly due to the limited detection\nof Il7r transcripts. By applying RECODE, we were able to improve transcriptome resolution and\nenhance Il7r detectability. This re-analysis allowed us to resolve the apparent discrepancy\nbetween CD127 protein levels (as detected by CITE-seq) and Il7r mRNA expression, allowing\nfor the clear identification of CD127⁺ ILC1s (see revised Figure 2, D and E, and revised\nSupplementary Fig. 2B). Finally, the use of RECODE effectively resolved this discrepancy\nbetween CD127 protein expression and Il7r mRNA expression and enhanced the accuracy of the\nannotation of our cell populations.\n6. In Figure 2F, the authors gated CD127- ILC1 and NK cells together to assess IFN-γ expression.\nHowever, based on Figure E and previous studies, there are likely differences in the IFN-γ\nexpression potential between these two cell types. For more accurate analysis, it would be better\nto first distinguish ILC1 and NK cells based on EOMES expression. Following this, the ILC1\npopulation could be further subdivided according to CD127 expression levels for a more precise\nassessment of IFN-γ production in each group.\nAs suggested by the reviewer, we re-analyzed IFN-γ production by first distinguishing ILC1s\n4\nfrom NK cells based on Eomes expression. We then further subdivided the ILC1 population into\nCD127⁻ and CD127⁺ subsets. This refined analysis revealed that IFN-γ production by CD127⁺\nILC1s at 6 hr post-CLP was lower than that by CD127⁻ ILC1s under sham conditions (revised\nFigure 2, F and G). Furthermore, a direct comparison between CD127⁻ and CD127⁺ ILC1s at CLP\n6h demonstrated that IFN-γ production was more restricted in the CD127⁺ ILC1 subset (revised\nFigure 2, H and I).\nThis re-analysis directly addresses the reviewer’s concern by applying a more rigorous and\nbiologically relevant classification of ILC1 subsets. By separating ILC1s from NK cells and\nfurther stratifying them based on CD127 expression, we provide a clearer view of the functional\nheterogeneity within the ILC1 population. These findings support the conclusion that CD127⁺\nILC1s are functionally distinct from CD127⁻ ILC1s, particularly in the context of IFN-γ\nproduction during acute inflammation.\n7. I wonder why there is no analysis of CD127+ ILC1 in the sham group in Figure 2F. It would\nbe interesting to know if CD127+ ILC1 show not only numerical differences in the CLP group\nbut also changes in functional characteristics such as IFN-γ expression, or if CD127+ ILC1\ninherently produce low levels of IFN-γ, regardless of CLP. Additionally, investigating the\ndifferences in cell characteristics between these groups could be further explored by performing\na more detailed analysis of the single cell analysis data from Figure 2D, separating the Sham and\nCLP groups.\nIn the original Figure 2F, we did not include CD127⁺ ILC1s under the sham condition due to the\nlimited number of cells available, as there are very few CD127+ ILC1s in the MAT of sham\ncontrols. However, in response to the reviewer’s comment, we re-evaluated IFN-γ production by\nCD127⁺ ILC1s, including under sham conditions. This analysis revealed that CD127⁺ ILC1s\nexhibited lower IFN-γ production even in the absence of CLP-induced inflammation, suggesting\nthat this subset is intrinsically less capable of producing IFN-γ compared to CD127⁻ ILC1s (see\nrevised Figure 2F).\nTo further address the reviewer’s point, we also performed an additional analysis of the\nscRNA-seq dataset. Specifically, we focused on inflammation-related genes and visualized their\nexpression as z-scores, analyzed separately for the sham and CLP groups. This allowed us to\nexamine potential functional differences in gene expression profiles between conditions and\nclusters. These results are now reflected in the revised figures (see also revised Supplementary\nFig. 2D) and the revised manuscript (lines 117-119 on page 7, and lines 316-321 on page 15).\n5\n8. In figure 2C, the authors state that after 6 hours of CLP, number of total ILC1 increase 2-fold\n(500 to 1000). In figure 3F and 3J, after parabiosis and spleen transplant experiments, the percent\nof ILC1 counterpart that the authors claim to derive from the spleen out of whole ILC1 increase\nfrom 4 to 10 percent for parabiosis experiments and 1 to 3 percent for spleen transplant\nexperiments. Which means that the spleen derived ILC1 cannot explain the 2-fold increase in total\nILC1 in MAT after CLP. Therefore, while it is reasonable to assert that some ILC1 migrate from\nthe spleen to the MAT, authors need to conduct additional experiment for explaining the 2-fold\nincrease in figure 2C. Moreover, since spleen-derived ILC1s constitute such a small population\nof the whole ILC1 population in the MAT in both sham and CLP condition, it is necessary to prove\nthat these cells are a critical contributor to the phenotypes observed.\nTo address the reviewer’s concern that spleen-derived ILC1s may not fully account for the\nobserved two-fold increase in total ILC1s (original Figure 2C), we performed an additional\nadoptive transfer experiment. Lin⁻ cells isolated from the spleen of CD45.2⁺ donor mice were\nintravenously transferred into CD45.1⁺ recipient mice (see revised Figure 3H). At 6 h post-CLP,\nthe frequency of donor-derived ILC1s in the MAT was significantly increased compared to the\nsham control, while a decreasing trend was observed in the spleen. These results support the\ncontribution of a spleen-to-MAT migratory axis contributing to ILC1s accumulation during\ninflammation (revised Supplementary Fig. 3, C and D).\nTo more directly assess migration dynamics, we calculated a “migration percentage” for\nspleen-derived-ILC1s (Sp-ILC1s) into the MAT. The migration percentage was defined as\npercentage of donor-derived ILC1s recovered from the MAT relative to the total number\nrecovered from both the MAT and spleen: migration percentage = [number of donor-derived\nILC1s in the MAT of the recipient mouse] / [number of donor-derived ILC1s in the MAT + spleen\nof the recipient mouse] × 100. The migration percentage of spleen-derived ILC1s at CLP 6h was\napproximately 5% higher than under the sham condition (revised Figure 3I). While this elevated\nmigration percentage alone may not fully account for the two-fold rise in total ILC1 numbers, it\nis important to consider that the spleen harbors substantially more ILC1s than the MAT. Therefore,\neven a 5% shift in migration from the spleen could result in a relatively large number of cells into\nthe MAT, supporting the notion that the spleen-to-MAT migratory axis plays a key role in the\nexpansion of the MAT-ILC1s population during inflammation.\nThe exacerbated pathology observed in ILC1 KO mice suggests that circulating ILC1s play\na critical role in regulating the pathophysiology of peritonitis. However, we believe that migrated\nILC1s alone do not fully explain the disease pathology of peritonitis. Rather, both MAT-resident\nand recruited ILC1s likely contribute to disease suppression. Additionally, as discussed later\n(refer to page 20 of the rebuttal for our response to Reviewer #3), ILC1s may also migrate from\n6\nsources other than the spleen. We discuss this point in the revised manuscript (pages 16-17, lines\n348-356).\n9. If ILC1 are derived from spleen, authors should verify increased ILC1 circulation in blood with\nmarkers including CD127, CXCR3 and Ly6C.\nIn response to the reviewer’s comment, we analyzed circulating ILC1s in the blood during\nperitonitis. CXCR3-expressing ILC1s were detected in the blood under both sham and CLP\nconditions (Appendix figure 1D), with a trend toward increased ILC1 frequency at CLP 6h\n(revised Supplementary Fig. 4A). These circulating ILC1s exhibited low CD127 expression,\nwhich remained unchanged following CLP. Notably, however, the proportion of Ly6C⁺ cells\nwithin the CD127― ILC1 population increased at CLP 6h (revised Supplementary Fig. 4, B–D).\nThese findings support our hypothesis that CD127― Ly6C⁺ ILC1s migrate from the circulation\ninto the MAT during peritonitis and may contribute to the local inflammatory response.\n10. FACS data in figure 2B shows that CD127+ ILC1 constitute up to 60% of the whole ILC1\npopulation in MAT 6h after CLP. However, cluster 0 in the UMAP plot in figure 2D, which the\nauthors claim to be the MAT-CD127+ ILC1s does not seem to occupy 60% of the whole ILC1/NK\ngroup, and indeed it seems to be such a small population in the UMAP plot. Authors should clarify\nthe discrepancy between FACS and CITE-seq data.\nWe appreciate the reviewer’s insightful comment regarding the apparent discrepancy between the\nFACS and CITE-seq data. As shown in the original Figure 2B, flow cytometry analysis indicates\nthat approximately 60% of MAT-resident ILC1s express CD127 at CLP 6h. In contrast, the\nUMAP plot in the original Figure 2D includes not only ILC1s but also NK cells, which comprise\na substantial portion of the NK/ILC1 cluster and therefore visually reduce the relative\nrepresentation of CD127⁺ ILC1s in the UMAP.\nHowever, when specifically examining clusters 0 and 1, which correspond to CD127⁺ and\nCD127― ILC1s, respectively, no major inconsistency is observed between the flow cytometry\nand CITE-seq data. Once NK cells are excluded from the analysis, the proportions are reasonably\nconsistent between both datasets.\n11. While Ly6C, Cxcr3, and PDL1 are emphasized as key molecules in the manuscript, the authors\ndo not present transcriptomic data for these markers. Providing RNA-level expression data for\nthese molecules would not only complement the current findings but also offer a more\ncomprehensive understanding of their biological significance. Furthermore, since the earlier\n7\nfigures consistently distinguish between CD127+ ILC1 and CD127- ILC1 populations, it would\nbe more scientifically rigorous to compare the expression levels of these molecules within this\nestablished framework. This approach would strengthen the clarity and validity of the authors’\nconclusions.\nWe thank the reviewer for this valuable comment. As noted in our response to the comment 7,\nwe have provided transcriptome data showing the expression of Ly6C, CXCR3, and PD-L1 in MAT-\nresident ILC1s, based on Il7r expression (⁺ or ⁻), as well as in NK cells (see revised Supplementary\nFig. 2D). Specifically, we found that relative expression levels of Cd274 (encoding PD-\nL1), Pdcd1lg2 (encoding PD-L2), and Cxcr3 were high in the CD127+ ILC1s cluster (revised\nSupplementary Fig. 2D). In contrast, Ly6c2 expression was enriched in the CD127⁻ ILC1s cluster\nin the sham control (revised Supplementary Fig. 2D).\nThese transcriptomic findings support and complement our surface protein data and provide\nadditional insight into the molecular characteristics of ILC1 subsets in the MAT. Furthermore,\npresenting these comparisons within the previously established framework of CD127⁺ and\nCD127⁻ ILC1s enhances the clarity and strengthens the validity of our conclusions. These\nadditional data are now included in the revised Supplementary Fig. 2D.\n12. The authors demonstrated the role of the CXCR10-CXCR3 axis in ILC1 migration. While\nCXCL10 protein expression was assessed in the MAT, and CXCR3 expression on ILC1s was\nmeasured in the spleen, it has not been evaluated in the MAT. Therefore, it is important to confirm\nthe expression of CXCR3 on ILC1s within the MAT.\nWe thank the reviewer for this important comment. Based on the reviewer’s concern,\nwe\nexamined CXCR3 expression in MAT-resident ILC1s using the same approach as for Ly6C\nanalysis. We found that ILC1s exhibited high levels of CXCR3 expression not only in the spleen,\nbut also within the MAT and MLN (see Supplementary Fig. 3K in the revised manuscript). These\nresults confirm that CXCR3 is broadly expressed on ILC1s across multiple tissues, including the\nMAT, supporting the involvement of the CXCL10-CXCR3 axis in ILC1 migration.\n13. In lines 202-204, you said CD127+ ILC1s “drive TNF-α production” in γδ T cells through\nthe PD-1/PD-L1 pathway. This sentence contradicts your data and previous words in this paper.\nWe thank the reviewer for their careful reading of our manuscript and apologize for this error.\nThe sentence has been corrected accordingly in the revised manuscript as follows (page 11, line\n228)\n8\n14. In the Extended data Figure 5 experiment, is there any data on how many adoptively\ntransferred CD45.2 MAT-ILC1s were in the host MAT at CLP 6h?\nWe do not have data on the exact number of adoptively transferred ILC1s present in the host\nMAT at CLP 6h, due to technical limitations. In the generation of the PLZF bone marrow chimeric\nmice, CD45.2⁺ PLZF-deficient bone marrow cells were transferred into a CD45.1⁺ recipient\nmouse. Although the number of ILC1s was significantly reduced in the PLZF―/― BM chimeras,\na small number of residual MAT-ILC1s persisted. Therefore, it was not possible to reliably\ndistinguish these doner-derived CD45.2+ PLZF―/― ILC1s from the subsequently transferred\nCD45.2⁺ ILC1s, preventing accurate quantification.\n15. In the Extended data Figure 5 experiment, you used the bone marrow transfer to make an\nILC1-depleted mouse and transferred ILC1 to see the effect of the existence of ILC1. Why did you\ntransfer ILC1 from MAT of the CLP-induced mice? Your previous study shows that the splenic\nILC1s are migrated to MAT when CLP is induced. Transferring splenic ILC1s from healthy mice\nis better to show your hypothesis. Or transplant a PLZF-/- spleen or PLZF+/+ spleen from\nhealthy mice to PLZF-/- bone marrow transplanted mice to see the exact mechanism of the splenic\nILC1s.\nWe believe that both circulating and tissue-resident ILC1s contribute to disease regulation. The\nexperimental design shown in the original Extended data fig. 5 was intended to assess the overall\neffect of ILC1s localized in the MAT at CLP 6h (see original Extended data fig. 5). The purpose\nof this experiment was not to specifically address the function of migrated splenic ILC1s, but\nrather to investigate the role of MAT-ILC1s, including both resident and migrated populations,\nduring acute peritonitis.\nTo directly assess the contribution of spleen-derived ILC1s, we performed an additional\nadoptive transfer experiment, as shown in the revised Figure 3, H and I. In this experiment,\nwe\ndemonstrated the migration of splenic ILC1s to the MAT following CLP induction. We have also\nrevised the schematic diagram and the corresponding text in the manuscript to eliminate redundancy\nand improve clarity (Supplementary Fig. 7, A and F, and lines 262-270 on page 13).\n16. In Figure 6, TNF-α+ γδ T cells represent only a small subset of the total cells. It raises the\nquestion of whether γδT cells are the primary producers of TNF-α in response to CLP when ILC1s\nare absent. Also, to determine if TNF-α-producing γδ T cells regulated by ILC1s are the main\ncontributors to preventing excessive inflammatory responses, additional experiments such as γδ\nwould help clarify whether γδ T cells regulated by ILC1s play a central role in controlling\ninflammation in this context.\nWe thank the reviewer for this critical comment, which was also raised by Reviewers #3\nand #4.\nTo more clearly demonstrate the critical role of TNF in mediating inflammation regulated by\nILC1s, we conducted an additional experiment using ILC1KO mice (NcrgreenCre x Tbx21fox/flox)\ntreated with anti-TNF antibody, and disease severity was assessed at CLP 6h. Experimental details\nare provided in the revised Methods section (lines 390-402, pages 18-19). In this experiment. we\ncompared 3 groups: wild-type controls, ILC1KO, and ILC1KO mice treated with anti-TNF\nantibody (revised Figure 6L). Notably, anti-TNF treatment reduced disease scores in the\nILC1KO mice (revised Figure 6M). In addition, expression of Lcn2, a gene associated with\ninflammation, was elevated in ILC1KO mice, but remained low following anti-TNF treatment\n(revised Figure 6N). These findings suggest that suppression of TNF production, regulated by\nILC1s, plays a key role in controlling inflammation and disease severity.\nMinor comments:\n1. In the supplementary figure 2A, the authors wrote the protein level on the violin plot, while the\nviolin plots show mRNA expression value.\nWe appreciate the reviewer’s careful reading of our manuscript. However, we would like to\nclarify that the violin plots in Supplemental figure 2A, currently Supplementary Fig. 2A, indeed\ndisplay protein levels. The axis labels and figure legend correctly indicate that the value shown\nrepresents protein expression from data obtained by CITE-seq analysis.\n2. Given the overall flow of the paper, ILC1 is the most critical population. Why are there no\nmarker genes distinguishing the clusters in Figures 2D and 2E?\nAs described above, we were finally able to define the cell clusters corresponding to CD127+\nand CD127― ILC1s using the RECODE package. Application of RECODE enabled clear visualization\nof the gene expression profiles of each cluster in the form of a heatmap. Il7r and Rora emerged\nas representative marker genes for CD127+ ILC1s (revised Supplementary Fig. 2B).\n3. In line 130, authors referenced reports on the role of IL-7 in downregulating CD127 expression,\nand states that such results are consistent with their findings. Is the any reason why authors chose\nthe reference on T cells?\nfunction and are considered the innate counterpart of helper-type T cells (Eberl et al., Science\n2015, PMID: 25999512). Therefore, we cited a study on T cells, as ILCs share similar functional\nand developmental characteristics with T cells. We believe this reference is relevant for\nsupporting the concept of IL-7-driven downregulation of CD127 on ILC1s.\n4. Figure 3M and 3N should include data after CLP.\nWe have added the CLP 6h data and found that CXCR3 expression in splenic CD127― Ly6C+\nILC1s was decreased at CLP 6h (see Appendix figure 1E), suggesting that these cells may have\ndownregulated CXCR3 expression in response to systemic inflammation induced by CLP, which\ncould potentially reflect changes in migratory behavior or tissue localization. However, the\nrelationship between CXCR3 downregulation and ILC1 migration remains unclear, and thus we\nhave included these data in the Appendix.\n5. Authors should show proportion difference between sham and CLP 6h condition of the UMAP\ncluster in figure 2D.\nWe thank the reviewer for this comment. In response to the reviewer’s suggestion, we generated\nUMAP plots comparing the sham and CLP 6h condition and found no differences in cluster\nproportions between the two groups (see Appendix figure 1F).\n6. It would be helpful to label “Cont” and “a-PD-1 Ab” in Figures 5F and 5G respectively.\nThank you for the suggestion. We have added the labels “Cont” and “a-PD-1 Ab” in the revised\nFigure 5F.\n7. It would be better to consistently use either “CD127+ ILC1” and “CD127- ILC1\" with spaces\nor “CD127+ILC1” and “CD127-ILC1\" without spaces throughout the manuscript, as the current\nversion inconsistently mixes both formats.\nAs requested, we have revised the manuscript to consistently use the format with spaces (e.g.,\n“CD127⁺ ILC1” and “CD127― ILC1”) when referring to CD127 expression in ILC1s throughout\nthe manuscript.\n11\n8. In Extended Data Figure 4, there is no gating strategy provided for CD4, CD8, and γδ T cells.\nWhen presenting the PD-1 levels, it would be more appropriate to display these marker genes on\nthe y-axis. Alternatively, it would be helpful to include the pre-gating strategy for these\npopulations.\nAs requested, we have included the gating strategy for T cell populations and revised the figures\naccordingly to more clearly present the various T cell subsets. These updates are now reflected in\nthe revised Figure 5, C and D, as well as in the revised Supplementary Fig. 5C.\n9. Extended data Figure 4. C and D are not mentioned. It’s better to explain the data in the main\ntext or remove it.\nWe apologize for not describing the experiments shown in Extended data figure 4, C and D,\nin the original manuscript. These experiments are now presented as Figure 5, C and D, and are\ndescribed in the revised manuscript (page 11, lines 220-221).\n10. At line 202, it’s better to unify the terminology: Extended Fig. 4B to Extended data Fig. 4B.\nWe apologize for this oversight. In the revised manuscript, the figure previously referred to as\n“Extended data Fig” is now consistently labeled as “Supplementary Fig.”\n11. In line 218, the nomenclature “PLZF-BM chimera mice” appeared, but you transplanted\nbone marrow from both PLZF-/- and PLZF+/+ mice. It’s better to clarify what the PLZF-BM\nmice are.\nThank you for the suggestion. We have clarified the definition of “PLZF-BM mice” by providing\nmore detailed information in the figure legend (revised Supplementary Fig 7, A and F).\n12. In the Extended data Figure 5A, the scheme said that MAT-ILC1 or PBS were injected into\nboth the PLZF-/- chimera and the PLZF+/+ chimera. Is it true that you used the four-mouse\ncondition?: PLZF-/- chimera + MAT-ILC1, PLZF-/- chimera + PBS, PLZF+/+ chimera + MAT-\nILC1, and PLZF+/+ chimera + PBS. I’m very confused with the experimental scheme even after\nreading the figure legend. The presentation of the scheme should be improved, and the data below\nshould be clearly stated, comparing which mice and which mice.\nin the original manuscript (now revised as Supplementary Fig. 7A). To improve clarity and\neliminate redundancy, we have revised the schematic figure and the corresponding text in the\nmanuscript (revised Figure 7). The original schematic is divided into two patterns based on the\nfollowing experiments (revised Supplementary Fig 7, A and F)\nIn this experiment, we compared two groups: PLZF⁻/⁻ bone marrow chimera mice that\nreceived either MAT-ILC1s (isolated at CLP 6h) or PBS. Both groups subsequently underwent\nCLP treatment. Importantly, no PLZF+/+ mice were included in the ILC1 injection experiment.\n13. Do PD-1+ γδ T cells or TNF-α producing γδ T cells express RORγt or T-bet?\nWe characterized γδ T cells into four subsets based on the expression of RORγt and T-bet:\nRORγt⁺T-bet⁻ (RORγt⁺), RORγt⁺T-bet⁺ (DP), RORγt⁻T-bet⁺ (T-bet⁺), and double negative (DN)\n(see Appendix figure 1G). PD-1 expression was predominantly observed in the RORγt⁺ and DP\nsubsets (Appendix figure 1, H and I). Furthermore, PD-1 expression increased across all subsets\nfollowing CLP treatment (Appendix figure 1I).\n14. Line 358: it should be “adoptive cell transfer” rather than “adaptive cell transfer.\nThank you for pointing this out. We have corrected the terminology to “adoptive cell transfer” in the\nrevised manuscript (line 442 on page 20).\nReviewer #2 (Remarks to the Author):\nThis manuscript examines the role of CD127+ ILC1s in the mesenteric adipose tissue in a low\nmortality model of cecal ligation and puncture\nWe thank the reviewer for the critical reading of our manuscript.\nMajor comments:\n1. Globally, the manuscript often conflates association with mechanistic causation. There are a\nnumber of times when the authors find the two phenomena are associated, but this does not mean\nthat one causes the other.\nWe fully agree with the reviewer that association does not necessarily imply mechanistic caution,\nand we recognize that certain parts of the original manuscript may have conveyed causal\ninterpretation without sufficient clarification.\nmodel and other disease models, approaches such as the use of conditionally deficient mice,\nadministration of neutralizing antibodies, and adoptive cell transfer are widely accepted and\nestablished methods for inferring causal relationships in immune responses in vivo.\n2. The authors examine a few parameters in figure 1 at 6 hours and 24 hours and find that\ndifferences are greater at 6 hours than 24 hours and conclude that “the strongest inflammatory\ncondition occurs at around 6 hours.” This conclusion cannot be drawn. All they can conclude is\nthat inflammation is stronger at 6 hours than 24 hours as inflammation might be greater at 1 or\n3 or 8 or 12 hours than 6 hours and the authors did not examine for this. The same is true when\nthe authors state that bacterial invasion was maximally detected at 6 hours after CLP when they\nonly examined 6 and 24 hours.\nWe thank the reviewer for this comment; a similar concern was also raised by Reviewer #1\n(Comment 1). As addressed in our response to Reviewer #1, we evaluated disease severity scores,\nbody temperature, and IL-6 production in plasma at 3, 6, 9, 12, and 24 hours after CLP (revised\nSupplementary Fig. 1, A-C). These analyses consistently indicated that the disease severity\npeaked at 6 hours post-CLP within the observed time frame.\n3. The results state that IL-b is decreased 24 hours after CLP in figure 1D. This is not consistent\nwith what is in the figure.\nTo more precisely assess Il1b expression among the three groups, sham, CLP 6h, and CLP 24h,\nwe increased the number of biological replicates to better capture the in vivo inflammatory\nresponse. However, statistical analysis revealed no significant difference in Il1b expression\nbetween the 6h and 24h time points. Accordingly, we have removed the corresponding statement\nfrom the revised manuscript to avoid any misleading interpretation.\n4. Some of the n’s in figures are quite low. For instance, figure 1E appears to be n=3. It is difficult\nto conclude anything meaningful from such a low sample size.\nIn response to the reviewer’s suggestion, in the revised manuscript, we have increased the sample\nsizes across our experiments to improve the reliability of the data.\n5. Quantification should be shown for figure 1G.\nDNA from the whole MAT and performed qPCR targeting a universal bacterial DNA region.\nBacterial DNA was detected at both 6 and 24 h after CLP, with higher levels observed at 24 h\n(Appendix figure 2A), even though pathological severity was greater at CLP 6h, as described in\nresponse to comment 2 of Reviewer #1 and comments 2 of Reviewer #2.\nThis result suggests that bacterial DNA may accumulate in the MAT over time. However,\nsince this data are not directory related to the mechanistic interpretation of our study, we have\ndecided to remove it from the main figures. Instead, we now present this result in Appendix figure\n2A.\n6. ILC-1 number are not different between 6 and 24 hours and are not different between sham\nand 24 hours. It may or may not be that the differences seen between sham and 6 hours are\nmeaningful based upon this.\nAlthough no significant difference was observed between 6 and 24-hour time points in total ILC1\nnumbers, this does not imply that the ILC1 response induced at CLP 6h is biologically\ninsignificant. In fact, CD127⁺ ILC1s were prominently induced at CLP 6h and persisted at lower\nlevels at 24 hours, whereas CD127― ILC1s significantly decreased over the same period.\nSince CD127⁺ ILC1s were originally rare in the sham control group, their persistence at 24\nhours can result in an apparently unchanged total ILC1 count, despite underlying compositional\nshifts between the CD127― and CD127+ subsets. Therefore, the lack of a statistical difference in\ntotal ILC1 numbers should not be interpreted as an absence of functional relevance in the\ninflammatory response.\nThe data regarding ILC1s at 24 hours after CLP have been added to the revised\nSupplementary Fig. 2A and are now discussed in the revised Discussion section (pages 14-15,\nlines 294-313).\n7. The conclusion on line 131 that the results “suggest that CD127 expression ILC1s was altered\nby the reduction of IL-7 in the MAT during acute inflammation, leading to an increase in CD127+\nILC1s at CLP 6h” is not supported by the data presented. As per point 1, correlation is not the\nsame as causation.\nIn response, we have revised the corresponding sentence in the manuscript to avoid conflating\nassociation with causation. We now present the observed correlation between IL-7 reduction and\nCD127+ ILC1 expansion more cautiously and without implying a direct mechanistic link in the\nrevised manuscript (page 8, lines 139- 141).\n15\n8. The parabiosis experiments are poorly described and difficult to understand.\nAs requested, we have added a more detailed description of the parabiosis experiments in the\nfigure legend for Figure 3D and revised the corresponding figure to improve clarity and facilitate\nunderstanding (revised Figure 3D).\n9. A decrease in splenic Ly6C+CD127- cells could potentially indicate migration but it could also\nindicate that these cells die – a possibility that is not considered in the manuscript.\nThank you for this critical comment. To address this point, we analyzed AnnexinV expression in\nLy6C+ CD127― cells and found that the expression levels were low compared to those in\napoptotic (dead) cells. This result indicates that splenic Ly6C+ CD127― cells were not undergoing\nsignificant cell death (Appendix figure 2B).\n10. The anti-CXCR3 experiments do not look at MAT. Therefore it is difficult to see how\nconclusions can be drawn regarding the MAT.\nIn the anti-CXCR3 treatment group, the number of ILC1s in the MAT did not change significantly\nfrom that in the isotype control group (Appendix figure 2C). However, we observed a positive\ncorrelation between the proportions of ILC1s in the spleen and the MAT. Notably, this correlation\nwas absent following CXCR3 blockade (revised Supplementary Fig. 3L), suggesting that\nCXCR3-dependent migration from the spleen to the MAT was disrupted.\n11. The data in figure 4D and E is also associative rather than proving causation.\nWe thank the reviewer for this comment. Figures 4, D and E were not intended to demonstrate a\ndirect causal relationship between ILC1s and γδ T cells. Rather, these data were presented to\nhighlight the functional role of ILC1s beyond IFN-γ production. We have revised the text to\nclarify this point (page 10, lines 206-207).\n12. Similarly, the data in Fig. 5F and G are also associative. While one certainly cannot refuse\nthe authors statement in the results that this indicates a “possibility” of a mechanistic relationship,\nthat is more speculative for the discussion.\nstating “direct cell-cell interactions were not demonstrated in this study” (page 14, lines 287).\n13. The ILC-1 deficient mice appear to be globally deficient as opposed to specifically in the MAT.\nAs noted by comment 15 of Reviewer #1, we believe that both tissue-resident and circulating\nILC1s contribute to the immune response in adipose tissue during peritonitis. The exacerbated\npathology observed in ILC1-deficient mice supports this concept.\nAlthough the ILC1-deficient model involves systemic deletion, we consider it appropriate in\nthis context, given the role of circulating ILC1s. To further address this limitation, we performed\nadoptive transfer of MAT-ILC1s isolated at CLP 6h into PLZF―/― BM chimera mice.\n14. While the authors acknowledge that figures 6C and D only show a “potential interaction”\nbetween ILC1 and gamma/delta T cells via the PD-PDL1 pathway in the MAT, there is also an\nassociation as opposed to a clear link.\nWe acknowledge that Figures 6, C and D show a potential, rather than definitive, interaction\nbetween ILC1s and γδ T cells via the PD-1/PD-L1 pathway in the MAT. However, our data show\nthat TNF production by γδ T cells is increased in both PD-1 blocked and ILC1s-deficient mice,\nand that PD-L1 expression on ILC1s is upregulated during peritonitis.\nBased on these findings, and in response to this comment as well as Reviewer #3’s minor\ncomment (comment 12), we have revised the Discussion section to clarify that while our results\ndo not establish direct cell-cell contact, they provide valuable insight into ILC1 biology (page 14,\nlines 287-293). These observations highlight the need for further studies to elucidate the\nmechanisms by which ILC1s regulate γδ T cells, potentially through co-stimulatory factors or\nother cytokine-mediated signaling pathways.\n15. Were mice given pain medicine? If so, this needs to be stated. If not, the reason for withholding\nthem needs to be clearly stated.\nThank you for this important comment. All animal procedures were conducted in accordance with\nthe institutional animal care and use protocol approved by RIKEN. Pain medication was not used\nin our experiments, as it was not required under the approved protocol.\nNevertheless, mice were closely monitored for signs of distress, including a drop in rectal\ntemperature exceeding 5 °C from baseline, abnormal posture, or sustained lateral recumbency. In\ncases where such endpoints were observed, animals were immediately euthanized.\n17\n16. Were data tested for a normal distribution? This is required prior to using a t test – otherwise\na non-parametric test should be used. If so, this should be included in the statistics section.\nOtherwise, this needs to be checked and the statistics redone (some of the groups are too small to\nhave a normal distribution).\nThank you for this important comment. We assessed the normality of each dataset using the\nShapiro–Wilk test, which is appropriate for small sample sizes. Non-parametric tests were applied\nwhere the normality assumption was not met. No major discrepancies were observed following\nthe reanalysis. Details of these statistical procedures have now been included in the revised\nMethods section (lines 577-583 on page 26).\nMinor comments:\n1. The first line of the introduction states that “peritonitis is a critical illness.” Peritonitis simply\nmeans inflammation of the peritoneum. Peritonitis could be associated with critical illness but\nmore often than not is not as most patients with acute abdomens do not end up in the ICU.\nWe thank the reviewer for this helpful comment. To address this point, we have revised the\nsentence to clarify that “peritonitis is an inflammation of the peritoneum caused by bacterial\nleakage from an intestinal perforation, leading to a severe acute inflammatory response” (page 3,\nlines 19-20 in the revised manuscript).\n2. What was the sex of mice used? This is not stated.\nIn our experiments, we primarily used female mice. Male mice were used only in experiments\ninvolving ILC1 KO mice and in the PLZF-BM chimera experiment to increase the sample size.\nWe have now added this information to the Materials and Methods section of the revised\nmanuscript (page 17, line 377).\n3. 10-25 weeks is a large span of mouse age ranging from young to middle aged. Why was such\na large span of ages used and were mice age matched in each experiment?\nIn most experiments, mice aged 10 to 15 weeks were used and were age-matched within each\nexperimental group. In the case of PLZF-bone marrow chimera mice, older donor mice were used\ndue to their acclimation period. This information has been clarified in the revised Materials and\nMethods section (page 21, line 453).\nIn the present manuscript Nagata et al investigated the role of ILC1s during peritonitis, by using\na model of cecal ligation and puncture (CLP). The authors show that upon inflammation the\nnumbers of ILC1s transiently increase in the mesenteric adipose tissue (MAT), alongside their\nexpression of CD127. These cells possess a unique phenotype producing less IFNg than their\nCD127- counterparts and expressing high levels of PD-L1, suggestive of a regulatory role. Indeed\nthe authors show that genetic ablation of ILC1s induces increased inflammation, as evidenced by\nmore TNF production by gd T cells and decreased body temperature, ultimately decreasing\nsurvival of the animals. Interestingly, the authors suggest that these “regulatory” ILC1s migrate\nfrom the spleen to the MAT in a CXCR3-dependent manner. The findings presented here are novel\nand part of them are supported by very elegant approaches. In my opinion, however, this\nmanuscript would benefit from additional experiments to strengthen the authors’ claims, as\ndelineated below.\nWe thank the reviewer for the supportive comments about our manuscript.\nMajor points:\n1. Even though Nagata et al used very interesting approaches to pinpoint a role for migration in\nthe ILC1 response during CLP (such as spleen transplants and parabiosis), I think some key\npoints need to be addressed. First, in Figure 1h, we observe that the numbers of ILC1 double at\n6h post CLP, however, in both the parabiosis and transplantation experiments, the frequency of\nILC1s coming from circulation is less than 10% (9% and 5% on average, respectively). Have the\nauthors checked for local proliferation? Also, could these ILC1s coming from other tissues such\nas the liver and gut? Upon CXCR3 blockade the authors observe an enrichment in ILC1s in the\nSpleen (suggesting that the cells are trapped there); but have the authors checked to see if CXCR3\nblockade prevents the increase in ILC1s in the MAT? Finally, I understand the difficulty of\nunderlying the spleen transplant experiment, but the n for that experiment seems quite low (so\nmuch so, that the difference in CD45.1+ ILC1s is not even significant) and I cannot find anywhere\nif/how many times that experiment has been repeated. As this supports a big conclusion of the\npaper, the authors should repeat this experiment to increase the n;\n- Still regarding the migration of ILC1s to the MAT, have the authors checked if blockade of\nCXCR3 induces an increase in cytokine production by gd T cells? What about the inflammatory\nresponse and survival of these mice?\nquestions were serially raised by the reviewer, but the central point, as we understand it, is the\nmechanism of ILC1s migration from the spleen to the MAT. We address each point in detail\nbelow.\nFirst, in Figure 1h, we observe that the numbers of ILC1 double at 6h post CLP, however, in both\nthe parabiosis and transplantation experiments, the frequency of ILC1s coming from circulation\nis less than 10% (9% and 5% on average, respectively). Have the authors checked for local\nproliferation?\nTo address this question, we assessed Ki-67 expression to evaluate local proliferation.\nCD127⁺ ILC1s at CLP 6h showed lower Ki-67 expression compared to CD127― ILC1s in the\nsham condition, suggesting that local proliferation is unlikely to be the main contributor to the\nobserved increase in ILC1 numbers (see revised Supplementary Fig. 3B).\nAdditionally, we conducted an adoptive transfer experiment in which CD45.2⁺ spleen-\nderived Lin― cells were transferred into CD45.1⁺ recipient mice, and we calculated the migration\npercentage (revised Figure 3, H and I), as also described in our response to Reviewer #1, comment\n16. The result indicated that approximately 5% of the transferred spleen-derived ILC1s detected\nin either the spleen or MAT were found in the MAT under inflammatory conditions. Considering\nthe large number of ILC1s in the spleen, even this modest migration rate could result in a\nsubstantial number of spleen-derived ILC1s accumulating in the MAT during peritonitis.\nAlso, could these ILC1s coming from other tissues such as the liver and gut?\nWe agree that migration from other tissues, such as the liver or gut, is one of the possibilities. In\nparticular, migration of liver-derived ILC1s via CXCR3 and CXCR6 has been previously reported\n(Wang, X. et al. Nat. Communications, 2018, PMID: 30451860). In our data, however, liver\nILC1s exhibited a distinct phenotype from those in the MAT or spleen (Appendix figure 3A and\nrevised Figure 2C). At CLP 6h, we observed no significant changes in total ILC1s, CD127⁻ ILC1s,\nor CD127⁺ ILC1s in the liver. Additionally, the proportion of Ly6C⁺ cells in the liver ILC1\nremained low (less than 20%) in both CD127ー and CD127⁺ ILC1s (Appendix figure 3B). These\nfindings suggest that if liver-derived ILC1s migrate to the MAT, their recruitment mechanism\nmay differ from that of spleen-derived ILC1s.\nRegarding potential migration of gut-derived ILC1s to the MAT, we have already discussed\nin the original manuscript (see line 279 in the original manuscript, currently lines 343-348 in the\nrevised manuscript). We have added the liver as an additional potential source of migrating ILC1s\n20\nin the revised manuscript (lines 348-356 on pages 16-17).\nUpon CXCR3 blockade the authors observe an enrichment in ILC1s in the Spleen (suggesting\nthat the cells are trapped there); but have the authors checked to see if CXCR3 blockade prevents\nthe increase in ILC1s in the MAT?\nActually, we found that CXCR3 blockade did not significantly alter the total number of ILC1s in\nthe MAT compared to the isotype control group (see Appendix figure 2C). As noted in our\nresponse above, the migration of ILC1s from the spleen to the MAT appears to be CXCR3-\ndependent, as evidenced by the disruption of the correlation between splenic and MAT ILC1s\nfollowing CXCR3 blockade (revised Supplementary Fig. 3L). However, we recognize that other\nmigratory pathways, such as CXCR6-mediated migration shown in another report (Wang, X. et\nal. Nat. Communications, 2018, PMID: 30451860), may also contribute to ILC1 recruitment to\nthe MAT. We have now discussed this possibility in the Discussion part of the revised manuscript\n(lines 348-356 on pages 16-17).\nFinally, I understand the difficulty of underlying the spleen transplant experiment, but the n for\nthat experiment seems quite low (so much so, that the difference in CD45.1+ ILC1s is not even\nsignificant) and I cannot find anywhere if/how many times that experiment has been repeated. As\nthis supports a big conclusion of the paper, the authors should repeat this experiment to increase\nthe n;\nWe thank the reviewer for this comment. In response to the reviewer’s suggestion, we have\nincreased the sample sizes across our experiments in the revised manuscript to improve the\nreliability of the data. All information for the number of experiments and sample sizes is included\nin each legend section of the revised manuscript.\nStill regarding the migration of ILC1s to the MAT, have the authors checked if blockade of CXCR3\ninduces an increase in cytokine production by gd T cells? What about the inflammatory response\nand survival of these mice?\nTo evaluate the downstream consequences of CXCR3 blockade, we further analyzed cytokine\nproduction by γδ T cells in the MAT. We observed that the number of TNF-producing γδ T cells\nwas not affected by CXCR3 blockade (Appendix figure 3, C and D). We therefore hypothesize\nthat blocking the CXCR3 pathway alone may not be sufficient to alter the TNF⁺ γδ T cell\nresponses, as tissue-resident ILC1s remain in the MAT even after CXCR3 blockade.\nregulated by multiple mechanisms beyond CXCR3 alone. For example, as mentioned above\n(page 21), both CXCR3- and CXCR6-mediated migration pathways may contribute to ILC1 recruitment.\nIndeed, we recognize the importance of investigating the functional consequences of CXCR3\nblockade, including its effects on cytokine production in the MAT, the overall inflammatory\nresponse, and survival. These are important questions that warrant further investigation in future\nstudies.\n2. Another important conclusion of the paper is that ILC1 suppression of gd-derived TNF restricts\ninflammation during peritonitis. Whereas by the CITE-Seq data it looks only gd T cells produce\nTNF (Extended Data Fig 4) the intracellular cytokine levels of TNF in gds seem very low (Fig\n5g) and even the total protein levels in the MAT is the lowest when compared to all the other\ninflammatory markers (Fig 1e). This raises the question if suppression of gd-derived TNF\nmediates the regulatory role of ILC1s. The authors should formally address the role of TNF in\nthe survival and regulation of body temperature of CLP mice, for instance by blocking TNF in\nthe Ncr1Cre X Tbx21Flox mice;\nWe thank the reviewer for this important comment, which was also raised by Reviewer #1\n(comment 16) and #4. To clearly demonstrate the important role of TNF in mediating\ninflammation regulated by ILC1s, we conducted an additional experiment using ILC1 KO mice\n(NcrgreenCre x Tbx21fox/flox) treated with anti-TNF antibody and assessed disease severity at CLP 6h.\nExperimental details are provided in the revised Materials and Methods section (page 18-19, lines\n390-402). We compared 3 groups: wild type, ILC1 KO mice, and ILC1 KO mice treated with\nanti-TNF antibody. A reduction in disease scores was observed in the anti-TNF-treated ILC1 KO\nmice group (revised Fig. 6, L-N).\n3. Is the acquisition of CD127 (and the associated regulatory phenotype, i.e. low IFNg production\nand PD-L1 expression) dependent only on the low IL-7 levels? If so, blocking IL-7 in naïve mice,\nor other inflammatory conditions that decrease IL-7 levels would also lead to the appearance of\nthese regulatory ILC1s. Finally, do the authors have a hypothesis for how low levels of IL-7 might\nsuppress the IFNg and increase PD-L1 expression?\nWe appreciate the reviewer’s critical comment about the role of IL-7 during peritonitis. To\ndirectly answer this question, we examined whether the level of PD-L1 expression is changed by\nrecombinant IL-7 (rIL-7) treatment. We found that rIL-7 treatment did not alter PD-L1 expression\non MAT-ILC1s at CLP 6h (see Appendix figure 3E). In addition, while IL-12 and IL-18, which\n22\nare cytokines known to stimulate ILC1s for IFN-g production, reduced CD127 expression when\ncells were co-cultured with rIL-7 (Appendix figure 3F). In contrast, IFN-g production itself was\nnot altered by the presence or absence of rIL-7 (Appendix figure 3G). These results indicate that\nboth PD-L1 expression and IFN-g production are largely IL-7-independent.\nTo explore alternative mechanisms, we examined the CITE-seq data. Our preliminary CITE-\nseq analysis indicated that Il7r+ ILC1s highly express Nr3c1, which encodes the glucocorticoid\nreceptor (revised Supplementary Figure 2B). Since glucocorticoids are known to suppress IFN-g\nproduction via Nr3c1signaling (Quatrini et al., J Exp Med. 2017, PMID: 29141867), we\nhypothesize that glucocorticoid-Nr3c1 signaling may contribute to the reduced IFN-g production\nobserved in CD127+ ILC1s. Additionally, Ifnar2, encoding a subunit of the type I interferon\nreceptor known to promote PD-L1 expression in several immune cell types (Bazhin et al., Front\nImmunol. 2018, PMID: 30356906), was relatively higher in the CD127⁺ ILC1s cluster (revised\nSupplementary Fig. 2D). Based on these observations, we thus hypothesize that PD-L1 expression\nin CD127+ ILC1s IFN-g may be regulated via type I IFN signaling. We have incorporated this\npotential mechanism involving glucocorticoid and type I interferons into the revised discussion\n(page 15, lines 314-321).\nMinor points:\n1. Bone marrow chimeras have a severe deficiency in the population of IL-17-producing gd T\ncells (Haas, Immunity, 2012) - which are the subset known to reside in adipose tissue. When\nworking with populations that are not radio-resistant, a way to overcome this problem is by\ninjecting neonatal thymocytes along adult bone marrow (Papotto, EMBO Reports, 2017). Have\nthe authors checked that the gd population in the MAT is comparable to that from non-bone\nmarrow chimeras? I.e., are they still able to produce IL-17 and TNF?\nIn this experiment, our aim was to compare the PLZF⁻/⁻ BM chimera mice with or without MAT-\nderived ILC1s. We confirmed that the frequency of γδ T cells in the MAT was comparable\nbetween PLZF⁻/⁻ and PLZF⁺/⁺ BM mice, as shown in the original Extended data fig. 5, D and E,\ncurrently Supplementary Figure 7, A-E. Therefore, we did not include non–chimeric (irradiated\nonly) mice in this analysis.\nAlthough we did not directly assess IL-17 or TNF production by γδ T cells, we detected\nexpression of RORγt, a master regulator of IL-17, in γδ T cells from PLZF⁻/⁻ BM mice (Appendix\nfigure 3H). Additionally, we found no difference in the number of MAT-derived γδ T cells\nbetween wild-type (B6) mice and PLZF⁺/⁺ BM chimeras (Appendix figure Fig. 3I).\nTaken together, these data suggest that the γδ T cell population is maintained in our BM mice\nmodel and remains available for functional response in the context of this study.\n23\n2. How do the authors explain that PD-L1 from ILC1s induce PD1 expression in gd T cells?\nCould the first be secreting another cytokine/factor that increases PD1 expression instead?\nWe thank the reviewer for raising this important point. We agree that PD-L1/PD-1 interaction\nalone may not fully explain the upregulation of PD-1 expression in γδ T cells. It is indeed possible\nthat PD-L1⁺ ILC1s secrete additional cytokines or co-stimulatory molecules that contribute to\nPD-1 induction.\nAlthough we did not directly assess these possibilities in the present study, we recognize\nthem as an important direction for future investigation. We have now added a statement discussing\nthis possibility in the revised Discussion section (page 14, lines 287-293).\n3. Do splenic CD127+ ILC1s also produce low levels of IFNg and express PD-L1?\nInterestingly, IFN-g production by splenic CD127+ ILC1s was increased at CLP 6h compared\nwith CD127― ILC1s in the sham control (Appendix figure 3J), which contrasts with the pattern\nobserved in MAT- CD127+ ILC1s. In addition, splenic CD127+ ILC1s also exhibited PD-L1\nincrease at CLP 6h. However, the expression level did not reach that of CD127+ ILC1s in the\nMAT (Appendix figure 3K).\n4. What happens to ILC1s to reach normal numbers at 24h post CLP? Do they die or do they\nmigrate somewhere else? Have the authors performed annexing staining or checked for CD45.1+\ncells in other organs from the parabiotic/transplanted mice, for instance?\nWe thank the reviewer for this comment; a similar question was also raised by Reviewer #2\n(comment 9). To explore the fate of ILC1s at CLP 24h, we examined Annexin V expression in\nMAT-ILC1s. The level of Annexin V remained low even at CLP 24h, suggesting that these cells\nwere not undergoing significant apoptosis (Appendix figure 3L). This finding raises the\npossibility that ILC1s may have migrated to other tissues rather than being eliminated by cell\ndeath.\nAdditionally, we observed that CD127+ ILC1s, which were induced at CLP 6h, persisted at\nreduced levels during the recovery phase at CLP 24h, suggesting that some ILC1s remained in\nthe MAT with altered phenotypic characteristics (revised Supplementary Fig. 2A). Although we\ndid not directly assess the distribution of CD45.1+ donor-derived ILC1s in other organs in the\nparabiotic or spleen-transplant models, this remains an important question for further\ninvestigation to elucidate ILC1 trafficking dynamics.\n24\n5. In the final point of their discussion the authors suggest that giving recombinant IL-7 could be\nbeneficial to patients with sepsis. However, wouldn’t this go against what the data shows?\nReduced IL-7 induces “regulatory” ILC1s that curb inflammation during sepsis?\nWe thank the reviewer for their critical comment. In the original manuscript, we discussed the\npotential of targeting MAT-ILC1s through rIL-7 administration to inhibit the immunosuppression\nobserved in the later pathological phase, as this is a major cause of mortality in septic patients.\nHowever, since the current study focuses on the early pro-inflammatory phase, we agree that this\ndiscussion could mislead readers regarding the applicability of rIL-7 treatment in the context of\nour findings. Therefore, we have removed this explanation from the original manuscript, lines\n296-300: “In addition to PD-1/PD-L1-targeted treatment, administration of recombinant human\nIL-7 to patients with sepsis has been attempted to sustain both CD4+ and CD8+ T cells during the\nimmunosuppressive phase. Thus, our results may also support the utility of rIL-7 administration\nin patients with sepsis in clinical trials”.\nReviewer #4 (Remarks to the Author):\nThis study by Nagata et al highlights the migration of ILC1s from the spleen to MAT and their\ninteraction modulating γδT cells via PD-1/PD-L1 during acute peritonitis. The findings\ncontribute to further understanding of migratory behaviours in ILCs, particularly ILC1’s, and\ntheir interaction with other immune cells namely gdT cells. Here, they identified the PD-1/PD-L1\nligand-interaction as the mechanism for ILC1’s controlling gdT cell-mediated secretion of TNF\nand subsequent inflammation.\nThe mouse model Ncr/Tbx21 is compelling in demonstrating the role of ILC1 in early timepoints\nin this peritonitis model and represent a useful mouse model for the field. Parabiosis and splenic\nsurgery are methodologically convincing to evidence of ILC1’s migration, further adding to the\nfield’s understanding of circulating vs tissue resident ILCs.\nWhile this study adds to immune cell function within AT, this reviewer suggests the following to\nbetter contextualise and support the study’s conclusions.\nWe thank the reviewer for the critical comments and suggestions on our manuscript.\n1. In determining the mechanistic crosstalk and what CD127+ PD-L1+ ILC1’s are acting on, the\nauthors primarily pursued PD1+ gdT cells and their increased TNF production. Could other cells\n25\nplay a (bigger) role: There is a risk of over-simplification on immune cell crosstalk here as the\nauthors only showed bulk CD4 and CD8 T cells not expressing PD1. Is there more data or\ndiscussion from gdT cell deficient models? More adequate analysis that other immune or\nT/innate-like T cell populations are not directly affected by migratory ILC1’s or express PD1 will\nbe more convincing, using analysis on the Ncr/Tbx21 mice, or at the very least discussed.\nCould TNF be a or one of many bystander effects of gdT cell activation? There is a risk of\ndisproportionate focus on TNF from gdT cells driving this acute pathology, as they constitute a\nrelatively minor population of ILC1’s/lymphocytes (eg <0.4% in Fig 5). Is this cytokine from gdT\nmore critical and specific to MAT immune responses during CLP? What’s the relative\ncontribution of total TNF increase by gdT cells against other cells? On the other hand, the critical\nrole of TNF seems to be downplayed in significance from the start (in Fig 1) prior to pursuing the\nTNF-producing gdT cells. Are there further evidence or discussion on functional contribution of\nTNF in TNF deficient or neutralisation? Furthermore, data on longitudinal tracking of gdT cells\nand whether their TNF/other cytokine production significantly change towards resolution or\nprogression across timeline post CLP could be informative.\nImportantly, details on number of mice and experiments are lacking from Fig 3 onwards across\nmanuscript and figure legends thus it is difficult to ascertain the data reproducibility and rigor.\nWe thank the reviewer for the critical comments and suggestions on our manuscript. While several\nquestions were raised by the reviewer, we understand that the central issue concerns the functional\nrole of TNF produced by gd T cells and its regulation by ILC1s in the MAT. We address each\npoint in detail below.\nIs there more data or discussion from gdT cell deficient models? More adequate analysis that\nother immune or T/innate-like T cell populations are not directly affected by migratory ILC1’s or\nexpress PD1 will be more convincing, using analysis on the Ncr/Tbx21 mice, or at the very least\ndiscussed.\nRegarding the relationship between ILC1s and other immune cells or T cell subsets in CLP mice,\nwe observed no significant differences in the numbers of TCRβ⁺ IL-17A⁺ or TCRβ⁺ IFN-g⁺ cells\nin the MAT between ILC1 KO and wild-type (WT) mice at CLP 6h (see Appendix figure 4A). In\ncontrast, we detected an increase of TCRβ⁺ TNF⁺ cells in ILC1 KO mice (Appendix figure 4A).\nHowever, whether ILC1s directly regulate these TCRβ⁺ TNF⁺ T cells remains unclear and\nwarrants further investigation.\nMeanwhile, PD-1 expression on γδ T cell subsets in the MAT was markedly elevated at CLP\n6h (see revised Fig. 5, C and D, and Supplementary Fig. 5C). However, no significant differences\n26\nin PD-1 expression were found in either RORγt― or RORγt⁺ T cell subsets between ILC1 KO\nand WT mice at this timepoint (Appendix figure 4, B and C). Considering the acute phase of the\nimmune response examined in our study, we hypothesize that γδ T cells are the primary direct\ntargets of ILC1-mediated suppression. Supporting this, as noted in our responses to Reviewer #1\nand #3, administration of anti-TNF antibody to ILC1 KO mice significantly ameliorated disease\nseverity. Together, these findings suggest that regulatory ILC1s control early-phase peritonitis by\nregulating TNF-producing T cells in the MAT. We recognize that further studies will be required\nto clarify the mechanisms of ILC1-mediated regulation and to fully address whether other\nT/innate-like T cell subsets are affected. We have now revised the Discussion and reflected these\npoints in the manuscript (page 14, lines 287-293).\nCould TNF be a or one of many bystander effects of gdT cell activation?\nIn the MAT, γδ T cells are known to produce both TNF and IL-17, indicating that TNF production\nis part of their physiological effector program rather than a non-specific bystander effect. In our\nstudy, while the number of IL-17A⁺ γδ T cells remained unchanged, TNF+ γδ T cells were\nsignificantly increased in ILC1 KO mice at CLP 6h (revised Fig. 6, G-I). Furthermore, anti-TNF\ntreatment significantly ameliorated disease severity in ILC1 KO mice (revised Fig. 6, L-N).\nCollectively, these results suggest that TNF produced by γδ T cells plays a functionally relevant\nrole in the pathogenesis of acute peritonitis in our model, rather than representing a secondary or\nnon-specific bystander effect of γδ T cell activation.\nIs this cytokine from gdT more critical and specific to MAT immune responses during CLP? There\nis a risk of disproportionate focus on TNF from gdT cells driving this acute pathology, as they\nconstitute a relatively minor population of ILC1’s/lymphocytes (eg <0.4% in Fig 5). Is this\ncytokine from gdT more critical and specific to MAT immune responses during CLP? What’s the\nrelative contribution of total TNF increase by gdT cells against other cells? On the other hand,\nthe critical role of TNF seems to be downplayed in significance from the start (in Fig 1) prior to\npursuing the TNF-producing gdT cells. Are there further evidence or discussion on functional\ncontribution of TNF in TNF deficient or neutralisation?\nAs noted in our response to Reviewer #1 (comment 16) and #3 (major comment), we found that\nanti-TNF antibody treatment reduced disease severity in ILC1 KO mice, suggesting that ILC1s\ncontrol early-stage peritonitis by suppressing TNF-producing cells within the MAT. However, it\nis important to note that in addition to γδ T cells, other TNF-producing populations such as Th1\ncells and macrophages are also present in the MAT. Given that peritonitis represents a systemic\n27\ninflammatory response, it is unlikely that TNF derived specifically from MAT γδ T cells plays an\nexclusive or dominant role in the overall immune response. Indeed, as described above, TCRβ+\nTNF⁺ cells were also increased in ILC1 KO mice. Therefore, although our results suggest\nthat TNF production by γδ T cells is functionally relevant, we cannot conclude from our current\ndata that it plays a specific role distinct from other TNF sources in driving MAT immune\nresponses during CLP.\nWe have discussed this point as a limitation and future direction in the revised Discussion\nsection of the manuscript (page 14, lines 287-293).\nImportantly, details on number of mice and experiments are lacking from Fig 3 onwards across\nmanuscript and figure legends thus it is difficult to ascertain the data reproducibility and rigor.\nWe thank the reviewer for this comment. We have increased the sample sizes across our\nexperiments to improve the statistical rigor and reliability of the data in the revised manuscript.\nAdditionally, we have ensured that detailed information regarding the number of experiments and\nsample sizes is now included in the figure legend throughout the revised manuscript. We also\nrevised and expanded the figure legends for clarity and ease of understanding.\nMinor comments:\n1. It will be helpful to ensure consistencies of figure details, there are clear labels for some but\nnot others. Eg, Fig 2D, label the cells associated to the clusters and corresponding colours. Fig\n3 flow cytometry plots, pre gated on ILC or ILC1? PD-L1+ ILC1’s for Fig 4E. For Fig 5B, clearer\nfont sizes. For Fig 6G, just pre-gated on gdT cells?\nWe are sorry that the experiments shown in the original figures were not clearly described. We\nhave made the following revisions to improve consistency and readability across the figures.\n・Fig. 2, D and E: A legend was added to clearly indicate the corresponding cell types and their\nassociated cluster color, ensuring alignment between the cluster names and visual representation.\n・Fig. 3, B and E: To clarify that the flow cytometry plots represent gated ILC1 population, we\nadded appropriate labels as follows: (B) “MAT-ILC1”, (E) “MAT-ILC1s in CD45.2 partner”.\n・Fig. 5B: Font sizes were increased to enhance readability.\n・Fig. 6G: A note was added to indicate that the data represent \"MAT-γδT cells\".\n2. Were the effects on body temp measurement post CLP in mice receiving anti PD-1 treatment\nin Figure 5?\nwith anti-PD-1 antibody but observed no clear changes compared to isotype control mice\n(Appendix figure 4D). This suggests that, although PD-1 blockade may alleviate local\nimmunosuppression in the MAT, it was not sufficient to impact the systemic inflammatory\nresponse as reflected by body temperature. However, since survival of ILC1 KO mice begins to\ndecline after day 2, it remains possible that anti-PD-1 treatment could exacerbate disease severity\nat later time points, an effect we plan to investigate in future studies.\n3. Are these MAT PD1+ gdT cells the Vg6 subset (Edwards et al JEM 2023),and are the\nimplicated gdT cells a specific subset that were already in the AT? As an aside, some gdT cells\ncan express PLZF.\nThank you for this insightful comment. It has been reported that PLZF-expressing γδ T cells in\nadipose tissue are characterized by high CD3 expression (Kohlgruber AC et al., Nat Immunol.\n2018, PMID: 29670241). To assess this point, we analyzed CD3high γδ T cells in both PLZF+/+ and\nPLZF–/– BM mice. In our study, CD3 high γδ T cells were observed in both the CD45.1+\n(irradiated recipient-derived) and CD45.2+ (donor-derived) populations of PLZF+/+ BM chimera\nmice, although their frequency was lower in the CD45.1+ population (Appendix figure 4E). In\ncontrast, while CD3 high γδ T cells were still detected in the CD45.1+ population of PLZF-/- BM\nmice, this population was absent in the CD45.2+ fraction (Appendix figure 4E).\nThese findings suggest that the CD3high γδ T cell population in the MAT may originate from\nradio-resistant cells, and a portion of them may indeed be PLZF-dependent. Further\ncharacterization, including Vγ chain usage (e.g., Vγ6), would be needed to definitively identify\nwhether these cells correspond to the Vγ6 subset described in the adipose tissue.\n4. Please check for necessary references to support statements across the manuscript, eg lines\n261-268.\nAccording to the reviewer's comment, we have now added appropriate references to\nsupport the relevant statements on page 15, lines 324-328. These include references\nrelated to the regulatory effects of TNF on phenotype changes and leptin production by\nadipocytes (Sethi et al., FEBS Lett 2000; Kirchgessner et al., J Clin Invest 1997).\nEditorial items:\nConsistency and accuracy in cytokines:\n1. The official name for TNF has been just TNF, without the “alpha” suffix.\n2. Figure 2 Legend: IFN-restricted. Important to stipulate IFN-g. Check manuscript for\nconsistency and accuracy.\nWe are sorry for this error; ‘IFN’ should be ‘IFN-γ’. We have amended the revised manuscript\naccordingly.\n3. Reword to adoptive and not ‘adaptive’ transfer.\nWe are sorry for this error; ‘adoptive’ should be ‘adaptive’. We have amended the revised\nmanuscript accordingly.\nWe thank the reviewers for their careful reading of the manuscript and suggestions for\nimprovement. Guided by these suggestions, we have prepared a revised version of the manuscript,\nin which all changes from the previous version are indicated in red font. A point-by-point response\nto all comments made by the reviewers is found below.\nReviewer #3 (Remarks to the Author):\nOnce again I would like to thank the authors for addressing all the points I raised before. I fully agree\nwith their interpretation of the first two points I raised; the resulting textual changes clearly reflect\nwhat the data is showing.\nRegarding my third point, even though I fully agree that the % of TNF+ gd T cells is decreased over\nthe course of CLP, I respectfully disagree with the claim that the total number of TNF+ cells do not\nincrease with CLP. Looking at the data, we can see that the number of total TNF+ cells roughly\ndoubles at 6h. I understand that the data is not statistically significant, but I guess that is only because\nof the variability seen in the last group (have the authors checked if their data fits the assumptions of\nparametric tests? I.e. normal distribution and homoscedasticity). Moreover, it is difficult to prove a\nlack of differences with no replicates and only 3-4 mice per group. Without any further experiments\n(i.e., repeating Sup Fig 5E, or showing total TNF levels in the MAT), the authors will need to adapt\ntheir interpretation regarding the role of TNF+ gd T cells to the fact that this is a minor population\nthat is going in the opposite direction (decreasing) of the vast majority of the cells (seemingly\nincreasing).\nWe thank the reviewer for these critical comments. As the reviewer pointed out, we also acknowledge\nthat the total number of TNF⁺ T cells show an increasing trend following CLP. Accordingly, we have\nrevised the relevant sentence in the Results section to more accurately reflect this observation as\nfollows (see revised manuscript page 12):\n“We found that the total number of TNF⁺ T cells and F4/80⁺ cells remained unchanged, although TNF⁺\nT cells showed a trend toward an increase after CLP (Supplementary Fig. 5E, left and 5F).”\nRegarding the limited sample size and the interpretation of the TNF+ gd T cell data, we agree that,\ngiven the small number of animals per group and the lack of independent replicates, our conclusions\nregarding the role of TNF⁺ γδ T cells should be interpreted with caution. Accordingly, we have revised\nthe Discussion to include the following interpretation addressing the minor TNF+ gd T cells population\nduring inflammation as follows (please refer the revised manuscript page 15):\n“We also showed that the capacity of TNF production by γδ T cells is restricted following CLP-induced\ninflammation, showing a trend opposite to that observed in the majority of T cells. Although this may\npartly explain why overall TNF production in the MAT does not increase after CLP (Fig. 1E), the\npathophysiological contribution of ILC1-mediated modulation of TNF⁺ γδ T cells should be\ninterpreted cautiously. This is because γδ T cells represent only a minor TNF-producing subset, and\nγδ T cell depletion in the ILC1-deficient setting was technically challenging. These limitations\ncomplicate the interpretation of our data and remain to be addressed. In future studies, in vivo cell–\ncell interaction mapping approaches, such as those using LIPSTIC/uLIPSTIC mice (Nakandakari-\nHiga S et al., Nature 2024; PMID: 38448581), together with γδ T cell-specific TNF ablation models,\nshould help clarify direct ILC1–γδ T cell interactions and the pathophysiological impact of TNF⁺ γδ\nT cells during CLP-induced inflammation.”\nIn addition, we also revised the title and abstract to tone down the wording.\nReviewer #4 (Remarks to the Author):\nI appreciate the authors’ additional analyses they performed in response to the earlier concerns.\nWith the revisions incorporated particularly expanded TNF-related data, the moderated title and\nclearer discussion of mechanistic limitations, the manuscript now more accurately reflects the\nstrength and boundaries of the available data. I believe the study is improved is now better\npositioned to contribute constructively to understanding ILC1 biology in acute peritonitis.\nThank you very much for your careful review and for your constructive suggestions, which have\ngreatly improved our manuscript."}]

Decision letter