Paneth cell TNF signaling induces gut bacterial translocation and sepsis

Charlotte Wallaeys; Natalia Garcia-Gonzalez; Steven Timmermans; Jolien Vandewalle; Tineke Vanderhaeghen; Somara De Beul; Hester Dufoor; Melanie Eggermont; Elise Moens; Victor Bosteels; Riet De Rycke; Fabien Thery; Francis Impens; Serge Verbanck; Stefan Lienenklaus; Sophie Janssens; Richard S Blumberg; Takao Iwawaki; Claude Libert

doi:10.1016/j.chom.2024.08.007

. Author manuscript; available in PMC: 2026 Feb 27.

Published in final edited form as: Cell Host Microbe. 2024 Sep 6;32(10):1725–1743.e7. doi: 10.1016/j.chom.2024.08.007

Paneth cell TNF signaling induces gut bacterial translocation and sepsis

Charlotte Wallaeys ^1,^2,¹³, Natalia Garcia-Gonzalez ^1,^2,¹³, Steven Timmermans ^1,², Jolien Vandewalle ^1,², Tineke Vanderhaeghen ^1,², Somara De Beul ^1,², Hester Dufoor ^1,², Melanie Eggermont ^1,², Elise Moens ^1,², Victor Bosteels ^1,^3,⁴, Riet De Rycke ^2,⁵, Fabien Thery ^6,⁷, Francis Impens ^6,^7,⁸, Serge Verbanck ⁹, Stefan Lienenklaus ¹⁰, Sophie Janssens ^1,^3,⁴, Richard S Blumberg ¹¹, Takao Iwawaki ¹², Claude Libert ^1,^2,^14,^*

PMCID: PMC12938039 NIHMSID: NIHMS2140799 PMID: 39243761

SUMMARY

The cytokine tumor necrosis factor (TNF) plays important roles in limiting infection but is also linked to sepsis. The mechanisms underlying these paradoxical roles are unclear. Here, we show that TNF limits the antimicrobial activity of Paneth cells (PCs), causing bacterial translocation from the gut to various organs. This TNF-induced lethality does not occur in mice with a PC-specific deletion in the TNF receptor, P55. In PCs, TNF stimulates the IFN pathway and ablates the steady-state unfolded protein response (UPR), effects not observed in mice lacking P55 or IFNAR1. TNF triggers the transcriptional downregulation of IRE1 key genes Ern1 and Ern2, which are key mediators of the UPR. This UPR deficiency causes a significant reduction in antimicrobial peptide production and PC antimicrobial activity, causing bacterial translocation to organs and subsequent polymicrobial sepsis, organ failure, and death. This study highlights the roles of PCs in bacterial control and therapeutic targets for sepsis.

Graphical abstract

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In brief

Wallaeys et al. studied Paneth cells (PCs) during TNF-induced inflammation. TNF signaling through its P55 receptor on PCs triggers an interferon signature and disrupts the unfolded protein response, causing reduced production of antimicrobial peptides and decreased antimicrobial activity. This PC dysfunction causes gut bacterial translocation and sepsis.

INTRODUCTION

The cytokine tumor necrosis factor (TNF) initiates signaling pathways by interaction with two receptors: TNF receptor 1 (TNFR1 or P55) or TNF receptor 2 (TNFR2 or P75). P55 is expressed on most cells, while P75 is inducible and restricted mainly to immune cells.¹ P55 stimulation leads to inflammation and cell death and is most important in pathology.² TNF holds a unique position among cytokines due to its wide array of activities. It kills tumor cells, but its use in systemic anticancer treatment is impeded by its pro-inflammatory properties, leading to the development of potentially fatal systemic inflammatory response syndrome (SIRS). Injections of TNF in human cancer patients revealed severe side effects, including hypotension, hepatoxicity, and gastrointestinal toxicity.³

Based on these studies and on TNF- or P55-deficient mice, TNF has been linked to a growing list of inflammatory disorders, such as Crohn’s disease (CD), ulcerative colitis (UC), arthritis, and psoriasis.^4–6 The mechanistic contributions of TNF in several forms of inflammatory bowel disease (IBD), however, are still a matter of debate.

TNF also plays a role in infection control. The lack of TNF or TNF receptors can increase the risk of infection in humans and mice, for example, with Listeria monocytogenes or tuberculosis.^7,8 By contrast, some studies (e.g., in primates using living Escherichia coli bacteria) have suggested that TNF is an important mediator in sepsis,⁹ and there is a tendency that the most severely ill sepsis patients respond favorably to TNF inhibition. Also, sepsis incidence is linked with single-nucleotide polymorphisms (SNPs) in the TNF promoter.¹⁰ Other studies (clinical trials in humans and studies in animals) have been unable to confirm a general role for TNF in sepsis.¹¹ IBD patients are at increased risk of infections and sepsis, possibly due to the aberrant immune response associated with the disease, the used immunosuppressive drugs, or the higher prevalence of surgeries.¹² Population studies showed a higher incidence of mortality from sepsis in patients with IBD compared with controls.¹³ A pattern arises linking TNF with occurrence of sepsis, but mainly when TNF is active in the intestinal compartment.^14,15

Injecting TNF in mice leads to a lethal sepsis-like SIRS, including acute diarrhea. This TNF effect is mediated by type I interferons (IFNs)¹⁶ (not type II IFNs¹⁷) and P55. Deletion of P55 on intestinal epithelial cells (IECs) is protective, even if only half of P55 expression is decreased.¹⁸ How this TNF toxicity is related with its function in severe sepsis is not known.

Paneth cells (PCs) are secretory cells in the crypts of Lieberkühn of the small intestine.¹⁹ They are crucial in regulating the composition of the enteric microbiota by secreting antimicrobial peptides (AMPs), such as a-defensins and lysozyme (LYZ1). Due to their high secretory activity, PC homeostasis relies on the unfolded protein response (UPR). X-box binding protein 1 (XBP1), an essential regulator of the UPR, is indispensable for PCs, as PC-specific deletion of XBP1 leads to intestinal inflammation.^20,21 Dysfunction or alterations in PC numbers have been associated with pathological conditions in humans, such as graft-versus-host disease,²² IBD,²³ and in mouse models.^24,25 PCs have been shown to be extruded into the crypts, and particularly IFNs have been shown to cause such effects.²⁶ The increased production of TNF in IBD patients may either cause an increased resistance to bacterial infections or an increased vulnerability because TNF may compromise epithelial barriers or PC activities. This study is exploring the role of PCs in this conundrum.

To understand the role of TNF in infectious diseases, we demonstrated that a mouse model of TNF-induced lethal SIRS leads to various gut-related issues that are strictly P55 dependent.²⁷ We here generated P55^PanethKO mice, which resist a lethal TNF challenge. RNA-seq and proteomics performed on pure PCs, sorted from mice, suggest that the robust UPR of PCs is compromised by TNF, leading to decline of a-defensins and reduced PC antibacterial activity. This TNF effect is P55- and type-I-IFN mediated and allows bacterial translocation to organs, such as liver, leading to polymicrobial sepsis, associated with typical sepsis features, such as metabolic collapse and multiple organ failure. We provide a perspective in sepsis research, proposing that an inflammatory response could undermine the microbiome-regulating functions of PCs, leading to sepsis.

RESULTS

PC-specific downregulation of Tnfrsf1a protects against TNF-induced lethal SIRS

P55 signaling in gut epithelial cells is a driver of TNF-induced inflammation in IBD and SIRS.^27,28 We confirmed this finding in P55^VillinKO mice using a model of lethal TNF injection (Figure 1G). To investigate the role of PCs, we applied a PC-specific Cre mouse line.²⁰ These Defa6-Cre transgenic mice were crossed with TdTomato (TdT)-reporter mice (Figure 1A): offspring expressed a PC-specific TdT signal (Figure 1B). Mice with reduced expression of Tnfrsf1a (P55) exclusively in PCs (P55^PanethKO) were generated by crossing Defa6-Cre mice with P55^fl/fl mice (Figure 1C). We observed reduced expression of Tnfrsf1a mRNA in PCs (identified with Lyz1 probe) of such P55^PanethKO mice (homozygous for the Cre allele and the P55^fl allele) via in situ hybridization (ISH) on ileum sections, compared with P55^fl/fl mice (denoted as P55^PanethWT, Figure 1D), but not in other IECs (Figure 1E). P55 mRNA was not entirely absent but significantly downregulated to 51% reduction. This reduction was also confirmed by RNA-seq on sorted PCs (Figure 1F). It has previously been demonstrated that a 50% reduction of P55 in mice is sufficient for protection against lethal TNF effects.¹⁸

P55^PanethKO mice, like P55^VillinKO mice, were protected against lethal TNF injections as compared with P55^PanethWT mice (Figure 1G). This protection is remarkable considering the low abundance of PCs in the small intestine. TNF-induced metabolic changes, studied at different time points after challenge (Figure S1A), suggest a systemic crisis with acute metabolic adaptations, including hypothermia and hypoglycemia (Figures S1B and S1C). In bacterial sepsis, the latter are indicative for a lack of hepatic gluconeogenesis and hepatic failure.^29,30 These metabolic adaptations were less pronounced in the P55^PanethKO than P55^PanethWT mice 18 h after TNF challenge (Figures 1H and 1I). In search of underlying mechanisms, we studied aspects of PCs and liver in P55^PanethWT and P55^PanethKO mice after TNF challenge (Figure 1J). When studying PCs by staining PC-specific LYZ1 protein, 18 h after TNF, PCs were still observed, although in slightly reduced numbers (Figure 1K), confirmed by TdT staining in TNF-treated TdT^PanethTG mice. The latter also showed signs of PC extrusion (Figures 1L and 1M).

PC-specific P55 signaling is associated with PC changes, bacterial translocation, and IFN responsesin PCs

Morphological PC changes by TNF were studied via transmission electron microscopy (TEM, Figure 2A). PBS-injected mice displayed no PC changes or extrusion. After TNF, P55^PanethWT mice underwent morphological changes of PCs and luminal extrusions (Figure 2B). The debris was clearly from PC origin as it contained secretory granules (red arrow, Figure 2A). P55^PanethKO mice were devoid of debris, and PC morphology remained intact. PC extrusion has been linked with PC-IFN signaling.^26,31 We quantified (PC-specific) LYZ1 signal in PCs 18 h after TNF injection. Control ileum sections of P55^PanethWT and P55^PanethKO mice displayed healthy PCs (fan-shaped cells in the crypts), but TNF caused a disorientation of PCs in P55^PanethWT mice, leading to scattered and less clustered LYZ1. This phenomenon was much reduced in P55^PanethKO mice (Figure 2C). We quantified the average volume of LYZ1 signal, which was significantly reduced in P55^PanethWT after TNF but quite intact in P55^PanethKO mice (Figure 2D).

The TNF-induced reduction in ileal biological activity of LYZ1 was significant in P55^PanethWT mice but not in P55^PanethKO mice 18 h after TNF (Figure 2E). Since LYZ1 is an essential and very abundant AMP produced specifically by PCs, these results suggest that TNF-P55 signaling in PCs leads to a decrease in LYZ1 (and other AMPs) transcripts, protein, or quality of LYZ1 (and maybe other AMPs).

We then investigated bacterial translocation from gut into organs (Figures S2A–S2C). We focused on the liver, considering that liver toxicity and transcriptional changes are dose-limiting effects of TNF in patients and because liver is an essential target organ during bacterial sepsis.^3,30 Bacterial growth in liver lysates was found after TNF challenge in P55^PanethWT, but much less in P55^PanethKO mice (Figure 2F), a protection also observed in the P55^VillinKO (Figures S2D–S2F). Bacterial colonies from liver were identified by matrix-assisted laser desorption/ionisation - time of flight (MALDI-TOF) (Figure 2G) and found to be 55.8% Enterococcus fecalis, 22.5% E. coli, 17.4% Staphylococcus aureus, 2.9% Staphylococcus xylosus, 0.7% Lactobacillus gasseri, and 0.7% Staphylococcus nepalensis. All are commensals found in the ileum of mice,³² suggesting that PC-specific P55 signaling is involved in a TNF-induced dysregulated PC response, leading to PC changes and bacterial translocation.

Transcriptomic changes on a genome-wide level in PCs derived from P55^PanethKO and P55^PanethWT mice treated with PBS or TNF were studied: PCs were isolated via fluorescence-activated cell sorting (FACS) (Figure 2H) 3 h after challenge to capture early TNF effects. RNA-seq was performed on equal amounts of sorted PCs per condition, and the complete purity of the PC sorted population was confirmed via single-cell RNA-seq.³³ The Venn diagram (Figure 2I) represents overlap between genes that are upregulated (p < 0.05 and log fold change [LFC] > 1) and downregulated (p < 0.05 and LFC < −1) by TNF in PCs of P55^PanethWT and P55^PanethKO mice. Following TNF injection, upregulation (LFC > 1.0 and p < 0.05) of 1,135 genes was observed in P55^PanethWT PCs. Via Enrichr pathway analysis (MSigDB_Hallmark_2020),³⁴ activation of IFN-γ response (86 genes), IFN-α response (50 genes), and TNF-α signaling (80 genes) were observed (Figure S2G). Both IFN pathways share a redundant set of 40 genes (see Table S1 for all Enrichr analysis in this paper). Pathway analysis on the 1,344 downregulated genes revealed disruptions in cell cycle regulation and mitotic processes (Figure S2H). TNF caused unique upregulation of 383 genes in P55^PanethWT (p < 0.05, LFC > 1) PCs. These genes may reveal mechanisms behind the observed PC dysfunctions. Enrichr analysis found multiple pathways: again the three most significant pathways being the IFN-γ (30 genes) response, IFN-α response (20 genes), and TNF-α signaling (15 genes, Figure 2J). Both IFN pathways share 17 genes (Figures S2I and S2J). Pathway analysis on the 587 uniquely downregulated genes in the P55^PanethWT delivered no significant pathways. Homer motif analysis on the promoters of the 383 genes confirmed significant enrichment of IFN-stimulated response element (ISRE), NF-κB-p65, and IFN regulatory factor (IRF8, IRF2, and IRF1) motif-containing genes (Figure 2K).

To investigate if TNF leads to PC depletions, changes in PC-specific gene expression were studied in IEC biopsies, 9 h after TNF, and RNA-seq was performed. PC-specific genes (Lyz1, Mmp7, and 28 genes from the a-defensin family) in IECs remain stable after TNF, and no changes were observed (Figure 2L).

Microbiome depletion protects but does not prevent the TNF-induced IFN signature in PCs or the reduction of LYZ1 activity

Bacterial presence in the liver suggests a role of the microbiome in TNF-induced lethality. We conducted experiments in mice pretreated with antibiotics in drinking water (Figure 3A), as previously described.³⁵ Mice subjected to antibiotics displayed strong protection against lethal TNF doses (Figure 3B), attenuated hypoglycemic response (Figure 3C), and fewer morphological disturbances in the PCs compared with control mice (Figure 3D), although activity of the LYZ1 was still compromised (Figure 3E). Microbiome depletion was confirmed by fecal plating and absence of bacterial translocation to the liver (Figure 3F).

PCs were sorted from mice that were pretreated with antibiotics or normal drinking water and challenged with TNF or PBS (Figure 3G). The response of the 383 genes (Figure 2I) was studied in this PC RNA-seq. 291 genes of these 383 were significantly upregulated with LFC > 1 after TNF in antibiotics pretreated mice (Figure 3H). This outcome is overrepresented, with a 7.26-fold enrichment compared with chance (hypergeometric p value: 1.74 3 10⁻²¹). Enrichr analysis on these 291 genes (again) resulted in the IFN-γ response (31 genes), IFN-α response (19 genes, of which 18 genes redundant), and TNF-α signaling (13 genes) as top hits (Figure 3I). When plotting log₂ fold changes (LFC TNF versus PBS) of the 291 genes in control H₂O mice and antibiotics mice, or P55^PanethWT versus P55^PanethKO mice, informative regressions are observed, showing less TNF effect in P55^PanethKO and an induced (141%) response in antibiotics pretreated mice (Figure 3J). To illustrate this effect, a heatmap with the LFCs of the 291 gene selection was drawn for the three conditions (Figure 3K). These experiments indicate that pretreatment with antibiotics is unable to prevent the detrimental IFN signature and the reduced LYZ1 activity in PCs but can protect against TNF lethality, including bacterial translocation. The data suggest that in the TNF model, PC dysfunction alone causes no live-threatening issues, on condition that gut bacteria are absent.

PC-specific P55 induces a sepsis signature in the liver and kills mice via multiple organ failure

To investigate the effect of PC-specific TNF signaling on the liver, we performed RNA-seq on this organ (Figure 4A). The overlap between genes that were upregulated (p < 0.05 and LFC > 1) and downregulated (p < 0.05 and LFC < −1) by TNF in the liver of P55^PanethWT and P55^PanethKO mice is shown in the Venn diagram. TNF injection led to 1,511 genes uniquely upregulated in livers of P55^PanethWT mice (p < 0.05, LFC > 1) and 1,445 genes uniquely downregulated in P55^PanethWT (p < 0.05, LFC < −1, Figure 4B). These data demonstrate a huge impact of TNF/P55 on a relatively rare and distant cell type (PCs) on the response of liver to TNF.

Enrichr analysis (DisGeNET database) on the 1,511 uniquely upregulated genes in the wild type (WT) revealed upregulation of genes related to infection and bacterial diseases (sepsis, pneumonia, pneumonitis, and septicemia, Figure 4C; individual genes behind these pathways are summarized in Figure S3A). Motifs enriched in the promoters of these genes were linked to inflammatory transcriptional cues (e.g., Fos, activator protein 1 [AP-1]), nuclear factor [NF]-κB, Jun, Figure 4H). Transcription factor (TF) analysis (ChEA_2022 database) of the 1,445 genes, downregulated in P55^PanethWT mice, revealed a strong association with TFs retinoid X receptor (RXR), peroxisome proliferator-activated receptor alpha (PPARα), and liver X receptor (LXR) (Figure 4D). PPARα is also identified as a TF in the Homer analysis of the respective gene set (Figure S3B). Previous studies have found a major role of liver PPARα dysfunction in sepsis progression. PPARα disruption leads to lethal metabolic reprogramming, causing hypoglycemia and accumulation of fatty acids in tissues and blood, contributing to multi-organ failure.³⁰ The LFC inductions of a selection of genes associated with sepsis pathways are shown in the heatmap of Figure 4E, and the expression levels of C5ar1, Cxcr4, and Mmp8, three genes identified as sepsis genes and redundant in other sepsis-related diseases (Figure S3A, bold genes) in the DisGeNET database, were indeed upregulated in the liver of P55^PanethWT mice after TNF, but not in P55^PanethKO mice (Figure 4F). Since these genes are induced after TNF, the role of translocated bacteria was investigated. These genes were no longer induced by TNF in livers of antibiotics-treated mice (Figure 4G), which suggests that TNF induces a lethal bacterial sepsis, originating from bacteria escaping the small intestine, due to direct TNF effects on PCs.

To further investigate sepsis occurrence, defined as a “life-threatening organ dysfunction caused by a dysregulated host response to infection,”³⁶ we measured clinical markers of organ damage and metabolic parameters: these organ damage markers were induced after TNF, whereas in antibiotics-pre-treated (Figure 4I) and P55^PanethKO mice (Figure 4J), the induction of these markers was notably reduced.

Mice lacking the P55 receptor in hepatocytes (P55^AlbKO mice, Figure S3C), similar as P55^AlbWT mice, displayed lethality upon TNF injection, demonstrating that liver P55 signaling does not contribute to lethality (Figures 4K and 4L). These mice were not protected against hypoglycemia (Figure S3D), loss of LYZ1 activity (Figure S3E), bacterial translocation (Figure S3F), or increased sepsis genes (Figures S3G–S3I).

TNF-induced type I IFN signaling and its role in TNF-induced lethal sepsis

Expression of all IFN ligands was examined in sorted PCs of WT mice 3 h after TNF or PBS. Genes coding for the 13 IFN-α ligands, IFN-β, IFN-γ, or both IFN-λ ligands were not detectable (Figure 5A). The heatmap includes four other cytokines (Cxcl1, Ccl20, Il33, and Cclr2) with low expression and are induced by TNF in PCs but less in P55^PanethKO mice, while antibiotics pre-treatment does not significantly affect their induction. Ifnb1-reporter mice were injected with TNF or PBS and imaged before and after injection (Figure 5B). 3 h after TNF, an increased luciferase expression was observed (Figure 5C). The strongest induction was observed in the spleen, liver, and small intestine (Figure 5D). To identify the key cell type, we analyzed Ifnb1 mRNA levels via qPCR in the spleen, liver, mesenteric lymphnodes (MLNs), and ileum after TNF. The spleen exhibited robust and reproducible Ifnb gene induction after TNF (Figure 5E). This was the case in mice pretreated with normal drinking water, antibiotics, and clodronate (to deplete macrophages) and in P55^PanethKO and P55^PanethWT mice. As a control cytokine, we measured Il6 expression, which is (unlike Ifnb) mainly derived from macrophage (Figure S3J). The results confirm that TNF directly induces type I IFN in the spleen (and possibly other organs) in cells that form no part of the monocyte/macrophage/dendritic cell lineages. This induction is independent of the microbiome or PC P55.

The expression of all six IFN receptor genes is detectable in PCs by RNA-seq and is independent of P55 expression or microbiome (Figure 5F). Examination of the fold-induction of these genes by TNF reveals robust upregulation in WT mice and in antibiotics-treated mice, while this effect is less pronounced in P55^PanethKO mice (Figure 5G; Table S2). This indicates that a portion of the increase in IFN receptor genes is directly influenced by PC P55.

IFNAR1^KO mice were protected against TNF-induced SIRS in terms of survival and hypothermia as previously described¹⁶ (Figures 5H–5J). The ileal LYZ1 biological activity was not compromised in IFNAR1^KO mice after TNF, while this was clearly the case in the IFNAR1^WT (Figure 5K), and bacterial translocation into the liver was no longer observed (Figure 5L). Sepsis genes were not upregulated in IFNAR1^KO livers by TNF (Figures 5M–5O). These data suggest that type I IFN responses, induced by PC-specific P55 signaling, play a crucial role in undermining PC function, driving bacterial translocation, eliciting sepsis gene inductions in the liver leading to lethality.

High UPR response in PCs and impact of TNF in a P55- and IFNAR1-dependent way

RNA sequencing (RNA-seq) was conducted on both PC- and non-PC-fractions, isolated from crypts by FACS (Figure 6A), followed by pathway analysis on the upregulated genes specific in PCs (Figures 6B and 6C). The UPR emerged as the most upregulated pathway in PCs. The four UPR sensors (Ern1, Ern2, Atf6, and Eif2ak3), along with the chaperone gene (Hspa5) and Xbp1, were all significantly upregulated in PCs (Figure 6D), independent of P55 or the microbiome (Figure 6E).

We applied transgenic endoplasmic reticulum (ER) stress-activated indicator (ERAI) reporter ERAI^TG/+ mice.³⁷ In response to ER stress/UPR, inositol-requiring enzyme type 1 (IRE1) functions as an endonuclease to excise an a-typical intron of Xbp1-venus mRNA, leading to translation of a visible XBP1s-venus fusion protein. This allows to monitor IRE1 activity. In mouse ileum, the XBP1s-venus protein was clearly present in basal conditions, specifically in PCs (Figure 6F). This signal remained unchanged 3 h after TNF injection (Figure 6G) but was completely lost 18 h after injection of TNF (Figure 6H) when mice are moribund, bacteria are translocating to the liver, and PCs are still present in the crypts (Figures 1K–1M). When counting XBP1s-positive crypts/total in PBS and TNF conditions, a significant reduction is observed 18 h after TNF (Figure 6J). ERAI^TG/+ mice, which are P55^+/− or which are IFNAR1^KO resist the effects of TNF, while microbiome depletion still leads to a reduced XBP1s-venus signal (Figures 6I and 6J). This indicates that TNF and type I IFN signaling in PCs result in a complete inhibition of the Ern1 and/or Ern2 Xbp1 splicing pathway of the UPR.

TNF induces early and late IFN-pathway activation, disrupts UPR response, and reduces AMP levels in PCs

ERAI^TG/+ mice and LYZ1 activity assays reveal that TNF-induced UPR problems and LYZ1 biological activity decline are late phenomena (Figure S1D). To investigate the inherent antimicrobial activity of PCs, they were sorted 12 h after TNF treatment to perform a PC-specific antimicrobial activity assay (Figure 7A). Healthy PCs exhibit high antimicrobial activity, leading to low bacterial survival of Staphylococcus nepalensis when co-cultured, while PCs from TNF-treated mice had reduced antimicrobial activity (Figure 7B). To study late TNF effects, we sorted PCs at 15 h (the latest possible time) and compared them with the 3 h time point (Figure 7A). The Venn diagram represents the overlap between early and late genes that are upregulated (p < 0.05 and LFC > 1) and downregulated (p < 0.05 and LFC < −1) by TNF (Figure 7C). Pathway analysis on all late TNF-induced genes revealed consistency with the pathways identified for all early TNF-induced genes (Figure S2G). Once again, IFN-γ response, TNF-α response, and IFN-α response are standing out (Figure 7D). The latter gene ontology comprises 97 genes, 53 being upregulated by TNF in PCs, indicating strong type I IFN activity. The mTORC1 signaling pathway emerges in the top 10 of late TNF-induced genes. Previous studies demonstrated that this pathway can reduce IRE1 activity.³⁸ Pathway analysis of early-specific (357 genes), common (769 genes), and late-specific TNF-induced genes (1,478 genes) is shown in Figures S4A–S4C. Notably, mammalian target of rapamycin complex 1 (mTORC1) signaling emerged again as a late-specific TNF-induced phenomenon (Figure S4C). Downregulated pathways for early and late genes are displayed in Figures S2H and S4D.

Figure 7. — (A) Setup: PCs were sorted 3 and 15 h after TNF/PBS injections and RNA-seq was performed (n = 3–4). At 12 h, PCs were isolated to perform an antimicrobial activity assay. Mass spectrometry was performed on sorted PCs 15 h after an injection of 35 μg TNF/PBS.

(B) Bacterial survival of *Staphylococcus nepalensis* co-cultured with isolated PCs of TNF-treated (35 μg, 12 h) or PBS-treated mice (n = 4–8). The data are normalized against bacterial survival of bacteria co-cultured with non-PCs (control sample, set as 100%).

(C) Venn diagram representing the number and overlap of DEGs that are upregulated (p < 0.05 and LFC > 1) and downregulated (p < 0.05 and LFC < −1) in PCs 3 and 15 h after TNF compared with PBS.

(D) Enrichr/MSigDB_Hallmark_2020 pathway analysis on all genes that are upregulated 15 h after TNF.

(E) Scatterplot demonstrating the log₁₀ expression values of PC-specific genes (coding for α-defensins, Lyz1, Mmp7, and RegIII proteins) 15 h after PBS versus TNF. The black line represents the slope (r), as analyzed with linear regression.

(F) RNA-seq mRNA counts of key ER stress genes in sorted PCs 15 h after TNF or PBS.

(G) Heatmap depicting PC-specific proteins measured via MS in individual PC samples (n = 5).

(H) Workflow: PCs were sorted after an injection of 30 μg TNF or PBS in IFNAR1^KO mice (n = 3).

(I) Venn diagram representing overlap between genes that are upregulated (p < 0.05 and LFC > 1) and downregulated (p < 0.05 and LFC < −1) by TNF compared with PBS in PCs of WT and IFNAR1^KO mice.

(J) Enrichr/MSigDB_Hallmark_2020 pathway analysis on the 214 genes upregulated by TNF in IFNAR1^KO mice.

(K) Heatmap depicting LFC effects after TNF of key ER stress genes in WT and IFNAR1^KO mice. Log fold changes (LFCs) after TNF are shown. All bars mean ± SD. Each dot represents a single biological replicate (F). p values analyzed with one-way ANOVA (B), two-tailed Student’s t test (F), or Wald test (K). ****p < 0.0001, ***p < 0.001, **p < 0.01, *p ≤ 0.05.

See also Figure S4 and Tables S1 and S2.

When examining PC marker genes (Defa genes, Lyz1 and Mmp7) and Reg genes, we observed that mRNA levels remain quite stable after TNF stimulation at both 15 h (Figure 7E) and 3 h (Figure S4E). When studying critical genes of the UPR pathway at 15 h, we observed a modest increase in Hspa5, Eif2ak3, and Atf6 after TNF (Figure 7F), but a steep decrease of the IRE1 genes (Ern1 and Ern2), not yet evident at the 3 h time point, when Ern1 is even upregulated (Figure S4F). This is in line with the ERAI^TG/+ data. As the decline in LYZ1 activity and average LYZ1 volume is not due to reduced PC marker mRNA levels, and UPR seems to be heavily compromised at a late time point, we performed proteomics mass spectrometry (MS) on sorted PCs (Figure 7A). PCs sorted from TNF-treated mice exhibited significantly reduced levels of PC-specific proteins, including α-defensins, LYZ1, and MMP7 (Figure 7G; Table S3).

Finally, we performed PC RNA-seq 15 h after TNF and PBS challenge of IFNAR1^KO mice and compared them with WT PCs (Figures 7H and 7I). An attenuated response was observed. When examining the critical genes of the UPR pathway, there was no longer an upregulation of Hspa5, Atf6, and Eif2ak3, nor a strong downregulation of Ern1 and Ern2 (Figure 7K). Pathway analysis of the TNF-upregulated genes (214 genes) in IFNAR1^KO mice revealed that the IFN-α pathways retained their prominence (Figure 7J). However, when examining the IFN-α response, only 10.3% of the genes assigned to it were found to be upregulated in IFNAR1^KO after TNF. This stands in sharp contrast to the 54.6% observed in WT mice (Figure S4G).

DISCUSSION

Sepsis is defined as a life-threatening organ dysfunction caused by a deregulated host response to infection.³⁶ Yearly, 49 million people are hit by sepsis, and 11 million of these succumb.³⁹ This accounts to 20% of all deaths each year. The identification of essential mediators and mechanisms in sepsis has not led to innovative therapies since most patients are treated by organ support, resuscitation, and infection control by antibiotics or surgery.⁴⁰

Several studies suggested that TNF was an essential player in sepsis. Antibodies against TNF were able to protect in a primate model of E. coli-induced sepsis,⁹ and TNF injection in human volunteers^41,42 and mice⁴³ proved that TNF caused SIRS, potentially fatal, and associated with pathophysiological changes reminiscent to sepsis.⁴⁴ TNF inhibition also protected mice in endotoxemia models, but clinical trials with TNF inhibitors in humans were disappointing. Some trials, however, proved that TNF inhibition had some protective effect in the most severe sepsis cases, where higher TNF levels were present.⁴⁵ Also, certain TNF promoter SNPs were linked with more severe sepsis.⁴⁶

Injection of TNF in mice is done to understand its toxicity and how this might be relevant in microbial sepsis. P55 is expressed on all nucleated cells, and full P55^−/− mice proved to resist most TNF-induced effects in mice.^47,48 Since the major dose-limiting effects of TNF in humans and animals are hypotension, liver failure, diarrhea, and cell death in the intestines, IEC-specific P55^−/− mice were generated. These mice were protected against lethality, diarrhea, IEC cell death on the tips of the villi, villi shortening, and erosion.^18,27 A role for IECs in TNFs general induction of SIRS and death appeared obvious and was also confirmed to be essential in the increased sensitivity to TNF using mouse mutants, such as caspase-8^−/−,⁴⁹ Ripk1^−/−,⁵⁰ or A20^−/− mice.⁵¹ TNF is the driving molecule in many IBD patients. How, mechanistically, TNF leads to death of the organism by means of IEC effects has remained unclear. The TNF model applied in our studies provides deeper insights into TNF-driven intestinal pathologies.

In this study, we found that PC-specific P55 depletion is sufficient to protect mice against TNF-induced lethal SIRS. The data obtained here allow to build a conceivable model whereby TNF has direct effects on PCs and indirect effects via inducing type I IFNs in tissues and PC IFNAR1. The strong reduction in Ern1 and Ern2 expression leads to acute lack of IRE activity and lack of Xbp1 spliced protein. How exactly P55/IFNAR1 cause Ern1 and Ern2 gene downregulation is not yet clear, nor how this might lead to declined α-defensin protein levels and antimicrobial activity in PCs. The ensuing bacterial translocation causes activation of genes, associated with sepsis, in the liver. Several of these genes are known to be involved in sepsis progression: Mmp8, for example, codes for matrix metalloproteinase 8 (MMP8), which has been shown to be crucial in sepsis.^52,53 The fact that TNF effects on PCs determine sepsis signatures in the liver rather than the hepatocyte P55 is unexpected and supports the crucial nature of this limited cell population. Previous studies in mice linked dysfunction or genetic ablation of PCs to increased occurrence of bacterial translocation to peripheral organs.^24,54,55 Our data, using the TNF model support the critical role for PCs to prevent bacterial translocation, and that P55 can undermine this PC function.

The basic high UPR in PCs, discovered here using the ERAI reporter mice, may come as no real surprise given their high protein production, yet it is specific and, for instance, not observed in goblet cells. Ern1 and Ern2 encode IRE1α and IRE1β, respectively, which are essential for the IRE endonuclease activity that cleaves Xbp1 mRNA, leading to Xbp1s mRNA and protein.⁵⁶ Xbp1 is essential in PCs and is a potent TF that regulates important processes such as the production of ER chaperones, ER-associated protein degradation (ERAD), and stimulation of lipid synthesis (thereby assisting in the expansion of the ER).⁵⁷ Given that PCs are among the highest secretory cells of the IECs, their proper control over protein folding is important. The connection between PCs and ER stress in gastrointestinal inflammation has become evident by the observation of intestinal inflammation and disruption of PC homeostasis in mice deficient in key ER stress-regulating proteins, including anterior gradient 2 (AGR2^KO)⁵⁸ and XBP1 (XBP1^VillinKO),^20,21 the latter also associated with reduced antimicrobial activity in the crypts. Moreover, deletion of the Xbp1 gene exclusively in PCs (XBP1^PanethKO) results in a similar phenotype as XBP1^VillinKO, characterized by ileitis. This links intrinsic ER stress in PCs to the development of gut inflammation.^20,21

Interestingly, the PC-specific P55 KO mice (P55^PanethKO) had only partial reduction of P55, even with two alleles of Defa6-cre. This poor decline in P55 is likely the result of low Cre expression in PCs and could be considered problematic, but in previous work, we found that a 50% decline of P55 mRNA and protein (in P55^+/− mice) is subject to a non-linear gene dosage effect since such mice show equal resistance to TNF effects as full P55^−/− mice.^18,59

The transcriptional impact of TNF on PCs is substantial, but mainly the upregulated genes were successfully classified by pathway analysis tools. RNA-seq revealed type-II-IFN-, TNF-, and type-I-IFN-pathways being top-activated. Since the P55^PanethWT-specific genes, induced by TNF, were also determined by these three pathways, we studied the role of IFNs into more detail. In previous work, we discovered that a knockout of the type I IFN receptor, IFNAR1, as well as a knockout of IFN-β protected mice against TNF,^16,60 but not a knockout of the type II IFN receptor IFNgR.¹⁷ Under no condition, PCs were found to express IFN ligands, but TNF did increase expression of all six different IFN receptor genes. Finding the IFN-β-expressing cells was approached using Ifnb1-reporter mice and found to be several organs, including spleen. TNF-induced IFNb1 expression in the spleen was unaffected by antibiotics or clodronate. Since IFNAR1^KO mice, in our study, resisted all relevant TNF effects (microbial translocation, UPR, and Ern1 and Ern2 decline), but since PC P55 is also essential in these TNF activities, a joint stimulation of P55 and IFNAR1 in PCs appears to cause the PC defects. Interestingly, in cells, the cytomegalovirus was also shown to downregulate IRE1.⁶¹ RNA-seq analysis of PCs sorted from TNF-stimulated IFNAR1^KO mice showed that the transcriptional impact of TNF was greatly reduced and that the typically late TNF-induced pathway, mTORC1, was no longer activated in these mice. Future research will have to discover how P55/IFNAR1 manage to decrease Ern1 and Ern2 and IRE1.

In this study, broad-spectrum antibiotics have been applied to understand the role of microbes in TNF-induced lethal SIRS. The antibiotics cocktail was provided for 2 weeks, based on previous studies, and to ensure complete culture negativity in the mouse feces and all intestinal compartments.^18,27,51 Antibiotics protect against TNF-induced lethality and the induction of sepsis genes in liver, but not against TNF-induced IRE1 decline. The antibiotics also did not change IFN-b induction in spleen upon TNF or expression of IFNAR1 or UPR genes in PCs. Several studies have shown that long-term antibiotics may influence immune responses in mice, especially at the level of IFN biology and IFNAR1 regulation at the IECs,^62,63 but our data are more compatible with a role of microbes, not in affecting the PCs or their response to TNF or IFNs, but in translocating to organs and causing polymicrobial sepsis.

We have optimized PC sorting from small intestines in healthy mice, yielding some 30,000 cells (99.9% pure PCs as follows from single-cell RNA-seq), sufficient for bulk RNA-seq, proteomics, qPCR, or antimicrobial studies. Since the TNF model involves several cell types and organ systems, it has to be studied in vivo. Therefore, we chose to isolate and sort PCs (and liver cells) from mice rather than stimulating PC-containing organoids. Although crypt-based organoids might offer many advantages and have been instrumental in several innovative insights,⁶⁴ they also impose limitations and, in this project, might not have detected the contribution of IFN-β. Via its impact on PCs, TNF causes bacterial infection in peripheric organs, such as liver, leading to sepsis, associated with induction of sepsis-linked genes in liver and typical other features, such as decline in PPARα TF activity,⁶⁵ hypoglycemia, hyperlactatemia,⁶⁶ and multiple organ damage and death. TNF has been suggested to play a role in sepsis, which is a highly controversial issue. However, there is a link between severe intestinal damage and sepsis. A study identified bacteria in the MLN (region affected by the disease) of 33% of CD patients, while only in 2% of control patients.⁶⁷ Moreover, postoperative sepsis was monitored, and there was a trend that the incidence correlated in patients with bacterial translocations in both the serosa and the MLN.⁶⁷ Another study found systemic endotoxemia in 88% patients with UC and 94% patients with CD during clinical relapse. Interestingly, the presence of systemic endotoxemia correlates with disease activity, disease extent, and the detection of circulating TNF and soluble TNFRs.⁶⁸ Our study suggests that TNF may not be a mediator in the pathology of polymicrobial sepsis, but it may be an inducer of sepsis itself by causing bacterial translocation after causing PC issues.

Our data also suggest the potential therapeutic benefit of administering TNF- or P55-blockers for treating IBD, combined with IFN inhibitors, or compounds that protect Xbp1s (splicing or translation) in IBD to prevent bacterial spreading. This approach should specifically target PCs while minimizing the potential side effects associated with systemic TNF inhibitors.⁵⁹ Interestingly, celiac disease, an autoimmune enteropathy triggered by gluten, also involves dysfunctional PCs and reduced lysozyme activity.^69,70

In conclusion, our data demonstrate that TNF has a big impact on PCs, reducing the IRE arm of their essential UPR, leading to declined α-defensin protein expression and antimicrobial effect and bacterial translocation to the system, including liver, which in turn causes polymicrobial, lethal sepsis. The data redefine the role of TNF in sepsis since we demonstrate that it is not a mediator in sepsis but rather a causative agent of bacterial sepsis. Our data also identify PCs (and their UPR) as interesting targets in preventing bacterial translocation from gut lumen to the system.

RESOURCE AVAILABILITY

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Claude Libert (claude.libert@irc.vib-ugent.be).

Materials availability

This study did not generate new unique reagents.

Data and code availability

RNA-seq data have been deposited at the National Center for Biotechnology Information Gene Expression Omnibus public database (http://www.ncbi.nlm.nih.gov/geo/) and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD053044. Microscopy and other datatypes reported in this manuscript will be shared by the lead contact upon request.
This paper does not report original code.
Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Polyclonal rabbit RFP Antibody Preadsorbed	Rockland	Cat#600-401-379; RRID:AB_2209751
Goat anti-Rabbit IgG (H+L) secondary Antibody, Alexa Fluor^® 568 conjugate	Invitrogen	Cat#A-11011; RRID: AB_143157
Polyclonal rabbit anti-human lysozyme	Agilent	Cat#A0099; RRID:AB_2341230
Donkey anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor^™ 568	Invitrogen	Cat#A10042; RRID:AB_2534017
ImmPRESS^® HRP Horse Anti-Rabbit IgG Polymer Detection Kit, Peroxidase	Vector	Cat#MP-7401; RRID:AB_2336529
GFP/Venus antibody	Cell signaling	Cat#2956s; RRID:AB_1196615
APC-conjugated anti-mouse CD24 antibody (Clone M1/69)	Biolegend	Cat#101814; RRID: AB_439716
PE Rat anti-mouse CD117 (c-Kit) Antibody (Clone 2B8)	Biolegend	Cat#105808; RRID: AB_313217
Brilliant Violet 421TM anti-mouse CD31 Antibody (Clone 390)	Biolegend	Cat#102423; RRID:AB_2562186
Brilliant Violet 421 Rat anti-mouse CD45 (Clone 30-F11)	Biolegend	Cat#103133; RRID:AB_10899570
Brilliant Violet 421 Rat anti-mouse TER-119/Erythroid Cells (Clone TER-119)	Biolegend	Cat#116233; RRID:AB_10933426
Bacterial and virus strains
Staphylococcus nepalensis	Isolated in mice, this MS	N/A
Chemicals, peptides, and recombinant proteins
recombinant mouse TNF	VIB protein core	N/A
Clodronate	Liposoma	Cat#CP-005-005
RNAlater^®	Ambion	Cat#10427114
β-mercapto-ethanol	Sigma-Aldrich	Cat#441433A
Aurum Total RNA Lysis Solution	Bio-Rad	Cat#732 6802
Ampicillin	Sigma-Aldrich	Cat#A-9518
Ciprofloxacin	Sigma-Aldrich	Cat#17850-5G-F
Metronidazole	Sigma-Aldrich	Cat#M-1547
Vancomycin	Labconsult	Cat#V0155-5
antigen unmasking solution	Vector	Cat#VEC.H-3300
Advanced DMEM/F12 medium	Gibco	Cat#12634010
TrypLE^™ Express Enzyme (1X), phenol red	Gibco	Cat#12605010
Deoxyribonuclease 1 from bovine pancreas (DNase)	Sigma	Cat#DN25
UltraPure^™ 0.5M EDTA	Invitrogen	Cat# 15575020
Critical commercial assays
Aurum^™ Total RNA Mini Kit	Bio-Rad	Cat#7326820
iScript cDNA Synthesis Kit	Bio-Rad	Cat#1708890
RNAscope^® Multiplex Fluorescent Detection Kit v2	ACDBio	Cat#323100
RNeasy Plus Micro Kit, 74034, Qiagen	Qiagen	Cat#74034
EnzChek^™ Lysozyme Assay Kit	Invitrogen	Cat#E22013
SensiFAST SYBR No-ROX Kit	Bioline	Cat#BIO-98020
ImmPACT DAB Peroxidase Substrate	Vector	Cat#SK-4105
Deposited data
RNAseq (PC P55^PanethKO, 3 hours after TNF)	This MS	GEO: GSE237759
RNAseq (IECs, 9 hours after TNF)	This MS	GEO: GSE268933
RNAseq (Liver P55^PanethKO, 18 hours after TNF)	This MS	GEO: GSE237949
RNAseq (PC ABX, 3 hours after TNF	This MS	GEO: GSE237588
RNaseq (PC, 15 hours after TNF)	This MS	GEO: GSE267790
RNAseq (PC IFNAR1^KO, 15 hours after TNF)	This MS	GEO: GSE267927
RNAseq (PCs and non-PCs)	This MS	GEO: GSE269510
MS data (PCs, 15h after TNF)	This MS	PRIDE: PXD053044
Experimental models: Organisms/strains
Tg(Defa6-icre)1Rsb	Prof. Dr. Blumberg	MGI:5559374
Tnfrsf1a^tm1.1Gkl (referred to as P55^fl/fl mice in manuscript)	Prof. Dr. Kollias	MGI:3053140
B6.Cg-Gt(ROSA)26Sor^{tm9(CAG-tdTomato)Hze}/J (referred to as TdT^fl/wt in manuscript)	The Jackson Laboratory	RRID:IMSR_JAX:007909
B6.129S2-//nar7^tm1Agt (referred to as IFNAR1^KO in manuscript)	Prof. Dr. Dallmeier	RRID:MMRRC_032045-JAX
B6.Cg-Speer6-ps1^{Tg(Alb-cre)21Mgn}/J Mus musculus (Referred to as Albumin-Cre in manuscript)	Prof. Dr. Elewaut	IMSR Cat# JAX:003574, RRID:IMSR_JAX:003574
Tnfrsf1a^tm1Blt (Referred to as P55^fl/fl in manuscript)	Rothe et al.⁷	MGI:1861040
Tg(CAG-XBP1/Luc)23Tiw (Referred to as ERAI in manuscript)	Prof. Dr. Iwawaki	MGI:5432350
B6.Cg-Tg(Vil1-cre)997Gum/J (Referred to as Villin-Cre^tg/wt in manuscript)	The Jackson Laboratory	RRID:IMSR_JAX:004586
Oligonucleotides
qPCR primers (Table S4)	This MS	N/A
RNAscope^® Probe - Mm-Tnfrsf1a-C1	ACDBio	Cat#426541
RNAscope^® Probe - Mm-Lyz1-C2	ACDBio	Cat#415131-C2
Software and algorithms
GraphPad Prism v.10.1.2	GraphPad Software	RRID: SCR_002798
HOMER v5.1	Heinz et al.⁷¹	PMID: 20513432; RRID:SCR_010881
Volocity 6.3 3D Image Analysis Software	Quorum Technologies Inc.	RRID:SCR_002668
Enrichr	Chen et al.³⁴	RRID:SCR_001575
Dia-NN algorithm 1.8.2 beta 27	Demichev et al.⁷²	RRID:SCR_022865
qbase+ version 3.4	Biogazelle	RRID:SCR_003370
Other
Lactate plus meter	NOVA Biomedical	Cat#ALP10110
Lactate plus test strips	NOVA Biomedical	Cat#ALP10102
Glucose meetstrips FreeStyle Lite	Abbott	N/A
FreeStyle Freedom Lite glucose meter	Abbott	N/A
Light Cycler 480 Instrument	Roche	RRID:SCR_020502
Leica Autostainer ST5010 XL	Leica	RRID:SCR_023957

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STAR★METHODS

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Mice

All the executed animal experiments were approved by the ethical committee for animal welfare at the Faculty of Sciences (Ghent University, Belgium) and conducted following the regulator standards. Mice were randomly assigned to different treatment groups, with the investigator blinded to the group allocations throughout the experiment and subsequent analysis. Males and females were used, aged 7 to 16 weeks. The health status of all mouse lines was regularly monitored in accordance with FELASA guidelines.

Defa6-Cre (Paneth-Cre) and Tnfrsf1a^fl/fl (P55^fl/fl) mice were generated by one of us (Prof. Dr. Blumberg) or provided by Prof. Dr. G. Kollias (Alexander Fleming Biomedical Sciences Research Center, Vari, Greece) respectively. Homozygous P55^fl/fl Paneth-Cre ^wt/wt (P55^PanethWT) mice and P55^fl/fl Paneth-Cre^tg/tg (P55^PanethKO) were generated by crossing a Paneth-Cre^tg/wt mouse²⁰ with P55^fl/fl mice and further intercrossing the offspring. To generate the TdT^fl/wt Paneth-Cre^tg/wt (TdT^PanethTG) and TdT^fl/wt Paneth-Cre ^wt/wt (TdT^PanethWT), a TdT^fl/wt reporter was crossed with a Paneth-Cre^tg/wt mouse. IFNAR1^KO mice were a kind gift from Prof. Dr. K. Dallmeier (Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, Leuven, Belgium). ERAI venus mice (ERAI^TG/+) were generated by one of us (Prof. Dr. Takao Iwawaki). ERAI^TG/+IFNAR1^KO were generated by crossing an IFNAR1^KO mouse with ERAI^TG/+ mice and further intercrossing the offspring. The mice were housed in individually ventilated cages, maintained under normal housing conditions (22°C, 14/10 h light/dark cycle, dark phase starting at 9 pm) within a conventional animal facility, and provided unrestricted access to food (18% proteins, 4.5% fibers, 4.5% fat, 6.3% ashes, Provimi Kliba SA) and water. To generate P55^fl/fl Villin-Cre^tg/wt (P55^VillinKO) and P55^fl/fl Villin-Cre^wt/wt(P55^VillinWT), P55^fl/fl mice were crossed with Villin-Cre^tg/wt mice, and offspring was further intercrossed. The P55^fl/fl Albumin-Cre^Tg/wt (P55^AlbKO) and P55^fl/fl Albumin-Cre^wt/wt (P55^AlbWT) were generated by crossing P55^fl/fl mice with an Albumin-Cre ^tg/wt mouse (kindly provided by Prof. Dr. D. Elewaut) followed by further intercrosses. P55 ^−/− (Tnfrsf1a^tm1Blt)⁷ mice were crossed with ERAI^TG/+ mice in order to obtain ERAI^TG/+P55 ^−/+ mice. The mice were housed in individually ventilated cages maintained under normal housing conditions (22°C, 14/10 h light/dark cycle, dark phase starting at 9 pm) within a specific pathogen-free (SPF) animal facility and provided unrestricted food (18% proteins, 4.5% fibers, 4.5% fat, 6.3% ashes, Provimi Kliba SA) and water. C57BL/6J (WT) mice in other experiments were purchased from Janvier Labs (Le Genest, France) or bred in our conventional animal facility. Only female WT mice aged 8 to 10 weeks were used when mice were purchased.

Mice were injected intraperitoneally (i.p.) with recombinant mouse TNF. Mice were injected i.p. with an LD100 TNF dose in a volume of 200 μL/20g bodyweight. The LD₁₀₀ dose of TNF was determined before, and varies depending on the animal house, mouse strain and the batch of TNF. Doses are indicated in the figure legends. Recombinant mouse TNF was produced in Escherichia coli and purified in our laboratories with no detectable endotoxin contamination. For the Clodronate experiment, 200 μL Clodronate (5mg/ml, Liposoma) was injected i.p. 3 days before TNF injection. Mice were anesthetized with ketamine (100 mg/kg) and xylazine (10 mg/kg) before blood collection via cardiac puncture. Rectal body temperature was monitored. All mice were killed by cervical dislocation.

METHOD DETAILS

Sampling

Ileum samples for LYZ1 and Venus staining were first flushed with PBS, fixed overnight in 4% paraformaldehyde (PFA) and embedded in paraffin. Samples for TdT staining were flushed with PBS, fixed in 4% PFA for 1h, washed three times with PBS, incubated overnight on a rotator in 30% sucrose, and then embedded in Tissue-Tek O.C.T. compound before being stored at −80 °C. Liver and spleen samples for RNA isolation were stored in RNAlater^® (Ambion). PCs (15 000 cells per sample) for RNA isolation were stored in 350 μL RLT buffer (provided in the RNeasy Plus Micro Kit) with 1% β-ercapto-ethanol (Sigma-Aldrich). PCs (30 000 cells per sample) for MS were snap-frozen and stored at −80 °C. IEC samples for RNA-isolations were prepared as follow: approximately 5 cm of the distal ileum was dissected, flushed with cold PBS and incubated with aurum total RNA lysis solution supplemented with β-mercapto-ethanol on ice for 5 min, after which the inner part of the bowel was scraped out and snap-frozen in liquid nitrogen and stored at −80 °C. Blood was centrifuged at 3000 rpm for 15min at 4°C, the upper plasma layer was collected and stored at −80 °C until further processed.

Depletion of the gut microbiome by antibiotics treatment

C57BL/6J mice were pretreated with 1 g/l ampicillin (Sigma-Aldrich), 200 mg/l ciprofloxacin (Sigma-Aldrich), 1 g/l metronidazole (Sigma-Aldrich) and 500 mg/l vancomycin (Labconsult) in the drinking water for two weeks. The mice received their drinking water ad libitum. After two weeks, the absence of bacteria was confirmed by culturing fecal samples on Brain Heart Infusion plates.

Quantitative polymerase chain reaction (qPCR)

Spleen and liver RNA was extracted using the Aurum^™ Total RNA Mini Kit (Bio-Rad) and RNA concentrations were measured using the Nanodrop 2000 Spectrophotometer (Thermo Fisher Scientific). 1000 ng of RNA was used for synthesis of complementary DNA (cDNA) using the iScript cDNA Synthesis Kit (Bio-Rad). qPCR was performed using the SensiFAST SYBR No-ROX Kit (Bioline) on the Lightcycler^® 480 System (Roche). Primers were purchased from IDT Integrated DNA Technologies and the primer sequences used for qPCR are depicted in Table S4. The best performing housekeeping genes for the spleen and liver (Gapdh, β-actin and Hprt) were determined using the geNorm House Keeping Gene Selection Software from QBase (Biogazelle, Ghent). All data were analyzed using qbase+ version 3.4 and GraphPad Prism version 10.1.2. Results are given as relative expression values normalized to housekeeping genes and scaled to the geometric mean.

Immunohistochemistry

Paraffin blocks were sectioned at 5 μm using the HM340E Semi-automated microtome (Thermo Fisher Scientific). Deparaffinization and rehydration were performed in the Leica ST5010 Autostainer XL. The sections were then washed with PBS and antigen retrieval was performed with proteinase K in Ca-TE buffer (1/20) (15 min at 37°C). 5% donkey serum was diluted (1/100) in PBT (PBS + 0. 5% BSA + 0.1% Tween20) and used as blocking solution (30 min at room temperature (RT)). Polyclonal rabbit anti-human lysozyme (LYZ1, A0099, Agilent) in PBT (1/1000) was used as primary antibody (incubated overnight at 4°C) and after washing (PBS), donkey anti-rabbit Alexa Fluor^® 568 (A10042, Invitrogen) in PBT (1/500) was used as secondary antibody (1h at RT). Tissue was counter-stained with DAPI (Invitrogen, 1/1000 in PBS) for 15 min at RT. Slides were then mounted with polyvinyl alcohol + DABCO (Sigma). To test for nonspecific binding of the secondary antibody, a negative control was made per sample by leaving the blocking solution on the sample instead of adding the primary antibody. TdT staining was performed on cryosections. Cryoblocks were sectioned at 10 μm using the CryoStar NX70. Slides were air dried for 15 min at RT, and washed with PBS. Same protocol was used as previous described for LYZ1, starting from the serum step, but here 5% goat serum was used. Polyclonal rabbit RFP Antibody Polyclonal rabbit anti-RFP (Rockland) in PBT (1/1000) was used as primary antibody and goat anti-rabbit Alexa Fluor^® 568 (Invitrogen) in PBT (1/500) was used as secondary antibody. Microscopic images were taken with the ZEISS Spinning Disk confocal microscope.

Colorimetric immunohistochemistry

For Venus staining, paraffin sections were dewaxed and subjected to 20-min antigen retrieval using antigen unmasking solution (Vector) in a PickCell 2100 pressure cooker (PickCell Laboratories). After cooling for 2.5h, slides were treated with 3 H₂O₂ in methanol for 10 min. Primary GFP/Venus antibody (Cell signaling), diluted 1:100 in 1% BSA-PBS buffer, was applied overnight at 4°C. After PBS wash steps, slides were incubated with secondary antibody (ImmPRESS^® HRP Horse Anti-Rabbit IgG (Polymer Detection Kit, Peroxidase MP-7401 (Vector) at RT for 30 min. The bound antibody was visualized using ImmPACT DAB Peroxidase Substrate (Vector) for 2 min. The reaction was stopped using BIDI. Subsequently, H&E staining was conducted using the Leica Autostainer ST5010 XL, and samples were mounted with Depex (Sigma). Images were made with the Axioscan Z1 (Zeiss).

In situ hybridization

The RNAscope^® Multiplex Fluorescent Detection Kit v2 (ACDBio) was performed according to the manufacturer’s standard protocol for small intestine on paraffin imbedded ileum sections. Ileum sections were stained with RNAscope^® Probe - Mm-Tnfrsf1a-C1 (ACDBio) and RNAscope^® Probe - Mm-Lyz1-C2 (ACDBio).

LYZ1 signal quantification

For each cryosection, Z-stacks of 7–10 areas were imaged with a spinning disk confocal microscope (Zeiss), using a LD LCI Plan-Apochromat 25x/0.8 Imm Corr DIC M27 objective lens at a pixel size of 0.440 μm and at optimal Z-resolution (1μm). For the quantification of the LYZ1 signal in the samples, the following workflow was used in Volocity 6.3 (Quorum Technologies Inc.): The LYZ1 signal mask was identified by applying a threshold based on SD of the intensity (lower limit <5%). For all the identified LYZ1 signal mask, the voxel volume was computed throughout the Z-stack, and for each sample the mean average volume was calculated.

Tnfrsf1a signal quantification in PCs and IECs

Multiple Z-stacks (with a Nyquist optimized interval of 1,03 μm) were acquired with a 25x objective (LCI Plan-Apochromat 25x/0.8 Oil) on a Zeiss LSM 780 confocal microscope on randomly selected regions in the small intestine. For the quantification of Tnfrsf1a RNAScope signal in PCs, the following workflow was used in Volocity 6.3 (Quorum Technologies Inc.): The PC and Tnfrsf1a RNAScope signal mask was identified by applying an intensity threshold. To quantify the Tnfrsf1a RNAscope signal present in the PCs, an intersect command was applied on the mask of both populations. The result was expressed as the ratio of the total volume of the Tnfrsf1a signal in the PCs on the total volume of the corresponding PCs. To quantify the Tnfrsf1a RNAscope signal in other intestinal epithelial cells (IECs), the same method was used. However, to identify the mask corresponding to IECs, regions of interest (ROIs) were manually determined in the villi.

Detection of bacteria in different organs

18h after injection of mice with PBS or TNF, mice were euthanized and the liver lobe, spleen and MLN were isolated and collected in 1 ml sterile PBS. Samples for bacterial counting were lysed in sterile PBS using the Qiagen TissueLyser II (5 min; 20 Hz), cultured on LB plates and the colony-forming units per ml were determined after 24h of incubation at 37°C. The colonies were identified by MALDI-TOF.

PC sort

Mice were sacrificed by cervical dislocation, and a single-cell suspension was prepared from isolated small intestinal crypts and stained for PC sort, following the method described by Schewe et al.⁷³ The small intestine was isolated, opened longitudinally, and washed three times in PBS. The villi were scraped off using a glass slide, then cut into small pieces (2–5 mm) with a surgical blade. The samples were washed with PBS by pipetting up and down until the supernatants was clear. The washed tissue pieces were incubated with 2 mM EDTA (Invitrogen) in PBS for 45 minutes on a rotator at 4 °C. After incubation, the EDTA was removed from the tissue. Cold PBS was added, and the tissue fractions were vigorously pipetted up and down to detach the crypts, and the crypt-containing supernatant was collected. This step was repeated four times. Advanced DMEM/F-12 (ADF) medium was added to reach a final volume of 50 ml and the crypts were passed through a 70 μm cell strainer. Crypts were pelleted by centrifugation at 300 × g for 5 min at 4 °C (as always, unless otherwise stated). The pellet was then resuspend in 1ml ADF medium with 50 μg/ml Deoxyribonuclease 1 from bovine pancreas (DNAse) and incubated for 15min at RT. Subsequently, ADF was added to reach a final volume of 10ml and centrifuged. ADF was added to the pellet, and the mixture was centrifuged again at 80 × g for 3min. The pelleted crypts were resuspended in 1 mL TrypLE^™ Express Enzyme with 50 mg/mL DNAse and incubated at 32 °C for 2 min. DMEM/F-12 was added to a final volume of 10ml and crypts were dissociated into single cells by harshly pipetting up and down for a minimum of 5 times. Cells were centrifuged, and the pelleted single-cells were stained for 30 min in the dark on ice with fluorescently conjugated antibodies diluted in HBSS + 2% FCS: APC anti-mouse CD24 Antibody (1/125, 101814, BioLegend), PE anti-mouse CD117 (C-Kit) Antibody (1/250, 105808, BioLegend), Brilliant Violet 421TM anti-mouse CD31 Antibody (1/100, 102424, BioLegend), Brilliant Violet 510TM anti-mouse CD45 Antibody (1/100, 103138, BioLegend), Brilliant Violet 421TM anti-mouse TER-119/Erythroid Cells Antibody (1/100, 116234, BioLegend). Cells were pelleted, washed with HBSS + 2% FCS and pelleted again. The pellet was dissolved in HBSS + 2% FCS, and DAPI (1/1000) was added.

FACS: Optimal voltages for each fluorophore were determined prior to each experiment, and the CST was checked daily. Flow cytometry was performed with a 100 μm nozzle on a BD FACSAria^™ III Cell Sorter using BD FACSDiva^™ software. Debris and doublets were excluded by sequential gating on forward scatter area vs side scatter area, followed by forward scatter width vs forward scatter height, followed by side scatter height vs side width area. Viable cells were identified by exclusion of 4,6-diamidino-2-phenylindole (Molecular Probes, Grand Island, NY). PCs were FACS-enriched by sorting CD24⁺C-kit⁺SSC^Medium-High CD31⁻CD45⁻TER119⁻ cells. The cells were collected in 1ml sort buffer (50% ADF and 50% FCS). Non-PCs were FACS-enriched by sorting CD24⁻SSC^Low-High CD31⁻CD45⁻TER119⁻ cells. Afterwards cells were washed with PBS, centrifuged, and resuspended in 350μl RLT buffer (provided in the RNeasy Plus Micro Kit) containing 1% β-mercapto-ethanol.

PC RNA isolation

PC RNA isolations were performed by the RNeasy Plus Micro Kit (Qiagen) according to manufacturing conditions. Homogenization of the samples was done by 1min of vortexing.

Liver and PC transcriptomics analysis

The RNA was used for creating an Illumina sequencing library using the Illumina TruSeqLT stranded RNA-seq library protocol (VIB Nucleomics Core) and single-end sequencing was done on the NovaSeq 6000. The obtained reads were mapped to the mouse reference transcriptome/genome (mm39/gencode v28) with STAR (2.7.10a), read count were obtained during alignment using the STAR “–quantMode GeneCounts” option. Differential gene expression was assessed with the DESeq2 package, with the FDR set at 5%. RNA-seq data deposited at the National Center for Biotechnology Information Gene Expression Omnibus public database (http://www.ncbi.nlm.nih.gov/geo/). Motif finding for multiple motifs was performed using HOMER software (v5.1).⁷¹ The promoter region (start offset: −500; end offset: default) was used to search for known motifs.

Transmission electron microscopy

PBS-flushed ileum was cut in small pieces and immersed in a fixative solution of 2.5% glutaraldehyde and 3% formaldehyde in Nacacodylate buffer 0.1 M. The tissue was placed in a vacuum oven for 30 min and afterwards placed on a rotator for 3 h at RT. The fixative was replaced with fresh one, and samples were left rotating overnight at 4°C. After washing in ddH2O, samples were post-fixed in 1% OsO4 with K3Fe(CN)6 in 0.1 M Na-cacodylate buffer, pH 7.2. Following another wash step, the samples were dehydrated through graded series of ethanol, and bulk-stained with 2% uranyl acetate at the 50% ethanol step before embedding in Spurr’s resin. To select the area of interest on the block and to have an overview of the phenotype, semi-thin sections were first cut at 0.5 μm and stained with toluidine blue. Ultrathin sections of a gold interference color were cut using an ultramicrotome (Leica EM UC6), followed by a post-staining in a Leica EM AC20 for 40 min in uranyl acetate at 20°C and for 10 min in lead stain at 20°C. Sections were collected on formvar-coated copper slot grids. Grids were viewed with a JEM 1400plus transmission electron microscope (JEOL, Tokyo, Japan) operating at 80 kV.

Lysozyme activity assay

Prior to the Lysozyme activity assay, approximately 5 cm of the distal ileum was dissected and underwent thorough washing with PBS. After removal of the residual PBS, samples were weighted and stored at −80 °C until further processed. Ileum samples were lysed in PBS using the Qiagen TissueLyser II (5 min; 20 Hz). Samples were then centrifuged at 10000 × g for 5 min and LYZ1 activity was tested on the supernatants via the fluorescence-based EnzChek^™ Lysozyme Assay Kit (Invitrogen), according to manufacturing instructions.

Antimicrobial activity assay

PCs and non-PCs were collected and sorted as previously described. A total of 25 000 PCs were sorted and resuspended in PBS, sonicated at 30 Hz and 40% of amplitude for 1 min. An overnight culture of Staphylococcus nepalensis was diluted to a ratio of 1:50 000. Subsequently, 500 μl of the bacterial suspension was further diluted 1:2 in the PC lysate, and the mixture was co-incubated for 4h at 37°C with agitation at 50 rpm. Following incubation, 100 μl of the mixture was cultured on LB plates, and the colony-forming units per ml were determined after 24h of incubation at 37°C.

Biochemical analysis

Blood glucose and lactate levels were measured in tail blood with the use of the Freestyle Freedom Lite glucose meter (Abott) and Lactate Plus meter (Nova Biomedical) respectively. Samples with glucose measurement below the detection limit were given a value of 20 mg/dl, which is the detection limit. The clinical chemistry markers for measuring organ damage (AST, ALT, CK, ureum, LDH, TroponinT and Creatinine) in plasma were measured by the University Hospital of Ghent.

Protein extraction and digestion for LC-MS/MS

Each replicate contains 30 000 PCs after sorting by flow cytometry. Cells were lysed in 50 μL of lysis buffer containing 8 M urea (Sigma-Aldrich, Merck, #U5378), 20 mM HEPES (Sigma-Aldrich, Merck, #H3375) at pH 7.5. Reduction and alkylation was performed with 13 mM tris(2-carboxyethyl)phosphine (TCEP) (Thermo Fisher Scientific, #20490) and 40 mM Chloroacetamide (Sigma-Aldrich, Merck, #C0267) after incubation at 55°C for 30 min under agitation and in the dark. Samples were diluted to 4 M urea with 20 mM Hepes pH 7.5. Proteins were digested with endopeptidase LysC (WAKO, #129–02541) for 4 h at 37°C under agitation. Samples were diluted to 2 M urea with 20 mM HEPES pH 7.5 and digested further with Trypsin (Promega, #V5111,) overnight at 37°C under agitation. Samples were acidified to 1 % Trifluoroacetic acid (TFA) (v/v) (Thermo Fisher Scientific, #85183) and further purified with C18 OMIX tips (Agilent Technologies, #A57003MB) according to manufacturer’s protocol. Purified peptides were dried under reduced pressure and stored at −20°C prior LC-MS/MS analysis.

LC-MS/MS analysis

Peptides were re-dissolved in 32 μL loading solvent A (0.1% TFA in water/ACN (98:2, v/v)) and 15 μL was injected for LC-MS/MS analysis on Ultimate 3000 RSLCnano system in-line connected to an Orbitrap Fusion Lumos mass spectrometer (Thermo Fisher Scientific). Trapping was performed at 20 μL/min for 2 min in loading solvent A on a 5 μm trapping column (Thermo Fisher scientific, 300 μm internal diameter (I.D.), 5 μm beads). The peptides were separated on a 250 mm Aurora Ultimate, 1.7μm C18, 75 μm inner diameter (Ionopticks) kept at a constant temperature of 45°C in a butterfly heater (Phoenix S&T). A Pneu-Nimbus nano source (Pheonix S&T) was used with a spray voltage set to 1.8kV and an ion transfer temperature of 275°C. Peptides were eluted by a non-linear gradient starting at 1% MS solvent B reaching 26.4% MS solvent B (0.1% FA in acetonitrile) in 75 min, 44% MS solvent B in 95 min, 56% MS solvent B in 100 min followed by a 5-min wash at 56% MS solvent B and re-equilibration with MS solvent A (0.1% FA in water), all at a flow rate of 250 nL/min. The mass spectrometer was operated in data-independent mode, automatically switching between MS and MS/MS acquisition. Full-scan MS spectra ranging from 390–910 m/z with a target value of 4E5, a maximum fill time of 50 ms and a resolution at of 60,000 were followed by 30 quadrupole isolations with a precursor isolation width of 10 m/z for HCD fragmentation at an NCE of 34% after filling the trap at a target value of 4E5 for maximum injection time of 54 ms. MS2 spectra were acquired at a resolution of 30,000 at 200 m/z in the Orbitrap analyser without multiplexing. The isolation intervals were set from 400 – 900 m/z with a width of 10 m/z using window placement optimization. QCloud has been used to control instrument longitudinal performance during the project.^74,75

Data analysis of LC-MS/MS

LC-MS/MS runs of all samples were searched separate using the Dia-NN algorithm (version 1.8.2 beta 27),⁷² library free. Spectra were searched against the human protein sequences in the Swiss-Prot database (database release version of 2024_04), containing 21,709 sequences (www.uniprot.org). Enzyme specificity was set as C-terminal to arginine and lysine, also allowing cleavage at proline bonds with a maximum of one missed cleavages. Variable modifications were set to oxidation of methionine residues. Default settings were used, except for the addition of a 395–905 m/z precursor mass range filter. Data were uploaded an visualized with clustviz webtool (https://biit.cs.ut.ee/clustvis/). Heatmaps show the Z-score as calculated by clustviz and are clustered based on correlation.

Graphical abstract

Graphical abstract was created with BioRender.com.

QUANTIFICATION AND STATISTICAL ANALYSIS

Statistical and graphical data analysis was performed using GraphPad Prism software 10.1.2. When comparing two groups, an unpaired two-tailed Student’s t-test was used. For comparing more than two groups with a control group, one-way ANOVA with Dunnett’s multiple comparisons was used. For comparing more than two groups with each other, one-way ANOVA with Tukey’s multiple comparisons test was used. For experimental setups that included a second variable, a two-way ANOVA followed by Šidák multiple comparisons test was used. Kaplan Meier survival curves were compared using a Log-Rank (mantel-cox) test. Statistics of the RNAseq were determined via DESeq2 (Wald test with FDR adjustment for multiple testing). P<0.05 was considered as statistically significant. ****P<0.0001, ***P<0.001, **P<0.01, *P%0.05, NS= not significant. N represents the amount of animals used for performing the experiment. All data is represented as mean±SD. qPCR data were first log-transformed as needed to obtain normal distribution. Statistical details are provided in the figure legends.

Supplementary Material

Figures S1–S4.

NIHMS2140799-supplement-Figures_S1_S4_.pdf^{(548.2KB, pdf)}

Table S1.

NIHMS2140799-supplement-Table_S1_.xlsx^{(510.7KB, xlsx)}

Table S2.

NIHMS2140799-supplement-Table_S2_.xlsx^{(11.2KB, xlsx)}

Table S3.

NIHMS2140799-supplement-Table_S3_.xlsx^{(1MB, xlsx)}

Table S4.

NIHMS2140799-supplement-Table_S4_.xlsx^{(11.4KB, xlsx)}

Supplemental information can be found online at https://doi.org/10.1016/j.chom.2024.08.007.

Highlights.

PC-specific TNFR1 (P55) mutant mice are protected against lethal TNF effects
PC-P55 signaling triggers an interferon signature and UPR failure in these cells
This UPR failure in PCs is IFNAR1 and P55 dependent but microbiome independent
PC-P55 UPR failure reduces AMP activity, causing bacterial escape and sepsis

ACKNOWLEDGMENTS

We thank Joke Van den Berghe and the animal care staff for animal care. We also thank Kelly Lemeire, HistoCore of the VIB Center for Inflammation Research for the help with immunofluorescent stainings. We thank the VIB Proteomics Core for liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The MS work was supported by Research Foundation Flanders (FWO, Odysseus grant G0F8616N to F.I. and fellowships to F.T. 12AN524N). The Horizon Europe supports this work with funding for the project BAXERNA 2.0 (101080544). Sequencing was performed by VIB Nucleomics Core. We like to acknowledge Amanda Gonçalves and Eef Parthoens (VIB BioImaging-Ghent) for technical support and data analysis. We thank the VIB flow core for training, support, and access to the instrument park. The research was supported by an FWO grant to C.W. (1S59421N). Further funding was obtained via FWO (SBO ZIPAM - S002721N) and the Research Council of Ghent University (BOF19-GOA-004 and Methusalem Program - BOF.MET.2021.0001.0).

Footnotes

DECLARATION OF INTERESTS

The authors declare no competing interests.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figures S1–S4.

NIHMS2140799-supplement-Figures_S1_S4_.pdf^{(548.2KB, pdf)}

Table S1.

NIHMS2140799-supplement-Table_S1_.xlsx^{(510.7KB, xlsx)}

Table S2.

NIHMS2140799-supplement-Table_S2_.xlsx^{(11.2KB, xlsx)}

Table S3.

NIHMS2140799-supplement-Table_S3_.xlsx^{(1MB, xlsx)}

Table S4.

NIHMS2140799-supplement-Table_S4_.xlsx^{(11.4KB, xlsx)}

Data Availability Statement

RNA-seq data have been deposited at the National Center for Biotechnology Information Gene Expression Omnibus public database (http://www.ncbi.nlm.nih.gov/geo/) and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD053044. Microscopy and other datatypes reported in this manuscript will be shared by the lead contact upon request.
This paper does not report original code.
Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

KEY RESOURCES TABLE

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Polyclonal rabbit RFP Antibody Preadsorbed	Rockland	Cat#600-401-379; RRID:AB_2209751
Goat anti-Rabbit IgG (H+L) secondary Antibody, Alexa Fluor^® 568 conjugate	Invitrogen	Cat#A-11011; RRID: AB_143157
Polyclonal rabbit anti-human lysozyme	Agilent	Cat#A0099; RRID:AB_2341230
Donkey anti-Rabbit IgG (H+L) Highly Cross-Adsorbed Secondary Antibody, Alexa Fluor^™ 568	Invitrogen	Cat#A10042; RRID:AB_2534017
ImmPRESS^® HRP Horse Anti-Rabbit IgG Polymer Detection Kit, Peroxidase	Vector	Cat#MP-7401; RRID:AB_2336529
GFP/Venus antibody	Cell signaling	Cat#2956s; RRID:AB_1196615
APC-conjugated anti-mouse CD24 antibody (Clone M1/69)	Biolegend	Cat#101814; RRID: AB_439716
PE Rat anti-mouse CD117 (c-Kit) Antibody (Clone 2B8)	Biolegend	Cat#105808; RRID: AB_313217
Brilliant Violet 421TM anti-mouse CD31 Antibody (Clone 390)	Biolegend	Cat#102423; RRID:AB_2562186
Brilliant Violet 421 Rat anti-mouse CD45 (Clone 30-F11)	Biolegend	Cat#103133; RRID:AB_10899570
Brilliant Violet 421 Rat anti-mouse TER-119/Erythroid Cells (Clone TER-119)	Biolegend	Cat#116233; RRID:AB_10933426
Bacterial and virus strains
Staphylococcus nepalensis	Isolated in mice, this MS	N/A
Chemicals, peptides, and recombinant proteins
recombinant mouse TNF	VIB protein core	N/A
Clodronate	Liposoma	Cat#CP-005-005
RNAlater^®	Ambion	Cat#10427114
β-mercapto-ethanol	Sigma-Aldrich	Cat#441433A
Aurum Total RNA Lysis Solution	Bio-Rad	Cat#732 6802
Ampicillin	Sigma-Aldrich	Cat#A-9518
Ciprofloxacin	Sigma-Aldrich	Cat#17850-5G-F
Metronidazole	Sigma-Aldrich	Cat#M-1547
Vancomycin	Labconsult	Cat#V0155-5
antigen unmasking solution	Vector	Cat#VEC.H-3300
Advanced DMEM/F12 medium	Gibco	Cat#12634010
TrypLE^™ Express Enzyme (1X), phenol red	Gibco	Cat#12605010
Deoxyribonuclease 1 from bovine pancreas (DNase)	Sigma	Cat#DN25
UltraPure^™ 0.5M EDTA	Invitrogen	Cat# 15575020
Critical commercial assays
Aurum^™ Total RNA Mini Kit	Bio-Rad	Cat#7326820
iScript cDNA Synthesis Kit	Bio-Rad	Cat#1708890
RNAscope^® Multiplex Fluorescent Detection Kit v2	ACDBio	Cat#323100
RNeasy Plus Micro Kit, 74034, Qiagen	Qiagen	Cat#74034
EnzChek^™ Lysozyme Assay Kit	Invitrogen	Cat#E22013
SensiFAST SYBR No-ROX Kit	Bioline	Cat#BIO-98020
ImmPACT DAB Peroxidase Substrate	Vector	Cat#SK-4105
Deposited data
RNAseq (PC P55^PanethKO, 3 hours after TNF)	This MS	GEO: GSE237759
RNAseq (IECs, 9 hours after TNF)	This MS	GEO: GSE268933
RNAseq (Liver P55^PanethKO, 18 hours after TNF)	This MS	GEO: GSE237949
RNAseq (PC ABX, 3 hours after TNF	This MS	GEO: GSE237588
RNaseq (PC, 15 hours after TNF)	This MS	GEO: GSE267790
RNAseq (PC IFNAR1^KO, 15 hours after TNF)	This MS	GEO: GSE267927
RNAseq (PCs and non-PCs)	This MS	GEO: GSE269510
MS data (PCs, 15h after TNF)	This MS	PRIDE: PXD053044
Experimental models: Organisms/strains
Tg(Defa6-icre)1Rsb	Prof. Dr. Blumberg	MGI:5559374
Tnfrsf1a^tm1.1Gkl (referred to as P55^fl/fl mice in manuscript)	Prof. Dr. Kollias	MGI:3053140
B6.Cg-Gt(ROSA)26Sor^{tm9(CAG-tdTomato)Hze}/J (referred to as TdT^fl/wt in manuscript)	The Jackson Laboratory	RRID:IMSR_JAX:007909
B6.129S2-//nar7^tm1Agt (referred to as IFNAR1^KO in manuscript)	Prof. Dr. Dallmeier	RRID:MMRRC_032045-JAX
B6.Cg-Speer6-ps1^{Tg(Alb-cre)21Mgn}/J Mus musculus (Referred to as Albumin-Cre in manuscript)	Prof. Dr. Elewaut	IMSR Cat# JAX:003574, RRID:IMSR_JAX:003574
Tnfrsf1a^tm1Blt (Referred to as P55^fl/fl in manuscript)	Rothe et al.⁷	MGI:1861040
Tg(CAG-XBP1/Luc)23Tiw (Referred to as ERAI in manuscript)	Prof. Dr. Iwawaki	MGI:5432350
B6.Cg-Tg(Vil1-cre)997Gum/J (Referred to as Villin-Cre^tg/wt in manuscript)	The Jackson Laboratory	RRID:IMSR_JAX:004586
Oligonucleotides
qPCR primers (Table S4)	This MS	N/A
RNAscope^® Probe - Mm-Tnfrsf1a-C1	ACDBio	Cat#426541
RNAscope^® Probe - Mm-Lyz1-C2	ACDBio	Cat#415131-C2
Software and algorithms
GraphPad Prism v.10.1.2	GraphPad Software	RRID: SCR_002798
HOMER v5.1	Heinz et al.⁷¹	PMID: 20513432; RRID:SCR_010881
Volocity 6.3 3D Image Analysis Software	Quorum Technologies Inc.	RRID:SCR_002668
Enrichr	Chen et al.³⁴	RRID:SCR_001575
Dia-NN algorithm 1.8.2 beta 27	Demichev et al.⁷²	RRID:SCR_022865
qbase+ version 3.4	Biogazelle	RRID:SCR_003370
Other
Lactate plus meter	NOVA Biomedical	Cat#ALP10110
Lactate plus test strips	NOVA Biomedical	Cat#ALP10102
Glucose meetstrips FreeStyle Lite	Abbott	N/A
FreeStyle Freedom Lite glucose meter	Abbott	N/A
Light Cycler 480 Instrument	Roche	RRID:SCR_020502
Leica Autostainer ST5010 XL	Leica	RRID:SCR_023957

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PERMALINK

Paneth cell TNF signaling induces gut bacterial translocation and sepsis

Charlotte Wallaeys

Natalia Garcia-Gonzalez

Steven Timmermans

Jolien Vandewalle

Tineke Vanderhaeghen

Somara De Beul

Hester Dufoor

Melanie Eggermont

Elise Moens

Victor Bosteels

Riet De Rycke

Fabien Thery

Francis Impens

Serge Verbanck

Stefan Lienenklaus

Sophie Janssens

Richard S Blumberg

Takao Iwawaki

Claude Libert

SUMMARY

Graphical abstract

In brief

INTRODUCTION

RESULTS

PC-specific downregulation of Tnfrsf1a protects against TNF-induced lethal SIRS

Figure 1. PC-specific downregulation of Tnfrsf1a protects against TNF-induced lethal SIRS.

PC-specific P55 signaling is associated with PC changes, bacterial translocation, and IFN responsesin PCs

Figure 2. PC-specific P55 signaling is associated with PC changes, bacterial translocation, and interferon responses in PCs.

Microbiome depletion protects but does not prevent the TNF-induced IFN signature in PCs or the reduction of LYZ1 activity

Figure 3. Microbiome depletion protects but does not prevent the TNF-induced interferon signature in PCs or the reduction of LYZ1 activity.

PC-specific P55 induces a sepsis signature in the liver and kills mice via multiple organ failure

Figure 4. PC-specific P55 induces a sepsis signature in the liver and kills mice via multiple organ failure.

TNF-induced type I IFN signaling and its role in TNF-induced lethal sepsis

Figure 5. TNF-induced type I IFN signaling and its role in TNF-induced lethal sepsis.

High UPR response in PCs and impact of TNF in a P55- and IFNAR1-dependent way

Figure 6. High UPR response in PCs and impact of TNF in a P55 and IFNAR1 dependent way.

TNF induces early and late IFN-pathway activation, disrupts UPR response, and reduces AMP levels in PCs

Figure 7. TNF induces early and late IFN-pathway activation, disrupts UPR response, and reduces AMP levels in PCs.

DISCUSSION

RESOURCE AVAILABILITY

Lead contact

Materials availability

Data and code availability

STAR★METHODS

EXPERIMENTAL MODEL AND STUDY PARTICIPANT DETAILS

Mice

METHOD DETAILS

Sampling

Depletion of the gut microbiome by antibiotics treatment

Quantitative polymerase chain reaction (qPCR)

Immunohistochemistry

Colorimetric immunohistochemistry

In situ hybridization

LYZ1 signal quantification

Tnfrsf1a signal quantification in PCs and IECs

Detection of bacteria in different organs

PC sort

PC RNA isolation

Liver and PC transcriptomics analysis

Transmission electron microscopy

Lysozyme activity assay

Antimicrobial activity assay

Biochemical analysis

Protein extraction and digestion for LC-MS/MS

LC-MS/MS analysis

Data analysis of LC-MS/MS

Graphical abstract

QUANTIFICATION AND STATISTICAL ANALYSIS

Supplementary Material

Highlights.

ACKNOWLEDGMENTS

Footnotes

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK