Introduction

Acetaminophen (APAP) overdose is the leading cause of drug-induced acute liver failure worldwide, resulting in over 10,000 hospitalizations and approximately 500 deaths annually in the United States.^1–4 The hepatotoxicity of APAP is initiated by its metabolic activation through cytochrome P450 enzymes, primarily in pericentral hepatocytes, generating the reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI).^5–8 NAPQI depletes glutathione and forms protein adducts, leading to oxidative stress and mitochondrial dysfunction that culminate in centrilobular necrosis.^5–8 Although the mechanisms of APAP bioactivation and toxicity are well-characterized, the early adaptive responses of hepatocytes—particularly their proliferative dynamics across lobular zones—remain poorly understood.

The liver is organized into functional hexagonal units termed lobules, where hepatocytes display spatial heterogeneity across three distinct zones: periportal (PP, zone 1), mid-zonal (Mid, zone 2), and pericentral (PC, zone 3).^9–11 These zones exhibit unique gene expression profiles and metabolic specializations.⁹ Pericentral hepatocytes (zone 3), expressing high levels of cytochrome P450 enzymes, are the primary site of acetaminophen (APAP)-induced necrosis.¹⁰ However, recent spatial profiling, functional, and lineage tracing studies have identified midzonal hepatocytes (zone 2) as the predominant source of new hepatocytes during both homeostasis and repair, demonstrating significant proliferative capacity and metabolic plasticity.^12–14 Despite these advances, how mid-zone hepatocytes dynamically adapt during the initial phase of acute stress remains unknown.

A key regulator of cellular stress adaptation is the integrated stress response (ISR), which phosphorylates eukaryotic initiation factor 2α (eIF2α) to suppress global translation while selectively upregulating stress-responsive genes, including activating transcription factor 4 (Atf4) and its downstream target pro-apoptotic factor C/EBP homologous protein (Chop, encoded by DNA damage-inducible transcript 3 [Ddit3]).^15,16 Although Chop is traditionally associated with apoptosis, its transcriptional targets exhibit significant overlap with those of Atf4, encompassing genes that paradoxically support cell survival and growth.^17–19 These findings underscore the context-dependent duality of the Atf4-Chop axis across different stress conditions, highlighting the need to elucidate its precise regulatory roles in specific physiological settings.

Through spatial transcriptomics (ST) and functional analyses, we demonstrate that zonal heterogeneity in APAP metabolism drives a stress-adaptive response in mid-zone hepatocytes during early AILI. This response is mediated by the Atf4-Chop-Btg2 axis, which orchestrates a transient proliferation arrest to prioritize cellular survival over regenerative capacity. Our findings elucidate the spatial and molecular mechanisms governing hepatocyte adaptation to acute injury, uncovering a critical survival-regeneration trade-off in early phase of acute liver injury.

Results

Mid-zone hepatocytes exhibit the most pronounced proliferative decline during early acute liver injury

To assess hepatocyte proliferation in early AILI, wild-type C57BL/6J mice were intraperitoneally injected with 300 mg/kg APAP, and liver sections were analyzed at multiple time points (0, 3, 6, 12, and 24 hours post-APAP). Immunohistochemical staining for Ki67, a proliferation marker, revealed that mid-zone hepatocytes exhibited a roughly 3-fold higher basal proliferative activity than PP and PC hepatocytes under homeostatic conditions (0 hour) (Figure 1A, B). During the early injury phase (3–12 hours post-APAP), the number of Ki67⁺ hepatocytes in the mid-zone sharply declined from 70 to 20 per section, reaching proliferation levels similar to those in PP and PC zones (Figure 1A, B). By 24 hours post-APAP, mid-zone proliferation gradually recovered (Figure 1A, B), indicating a transient suppression of proliferation in this region during early AILI. Further analysis of proliferation dynamics in each zone confirmed that all zones exhibited reduced proliferation during the injury initiation phase, with the mid-zone showing the most decline (Figure 1C). Comparative value change analysis (relative to 0 hour) further supported these findings, highlighting the mid-zone as the most affected region in terms of proliferative suppression during early AILI (Figure 1D).

Figure 1.

Mid-zone hepatocytes show distinct gene expression profiles with reduced proliferative activity during early acute injury

To investigate the mechanism underlying proliferation pause during early AILI, liver sections from wild-type mice treated with APAP for various time points were subjected to ST using the Visium (10 × Genomics) platform (Figure S1A). Due to variability in mice’s responses to APAP, multiple mice were treated at each time point, and the samples representing the average level at each time point were selected based on Hematoxylin and eosin (H&E) staining and serum alanine aminotransferase (ALT) levels for ST analysis. H&E staining of liver sections used for ST revealed a gradual increase in the necrotic area from 0 to 24 hours (Figure S1B). Spatial map analysis consistently and unbiasedly divided the liver into three zones (PP, Mid, and PC) across all time points (Figures S1C). Analysis of ST data at 0, 3, 6, and 24 hours post-APAP via UMAP plots consistently revealed distinct zonal clusters and dynamic spatiotemporal patterns during the early phase of acute injury (Figures S1D and S1E). Spatiotemporally resolved heatmaps of representative markers, such as Glul (a PC marker) and Cyp2f2 (a PP marker), further reinforced the stability of zonation profiles during early acute liver injury (Figure S1F). These findings suggest that while gene expression profiles change during acute injury, the fundamental spatial architecture of liver zones remains stable. Additionally, immunofluorescence staining of Glutamine Synthetase (GS, the protein product of Glul) and RNA-FISH for Cyp2f2 in liver sections collected at 6 hours post-APAP confirmed these ST analyses (Figure S1G).

We further analyzed differentially expressed genes (DEGs) in hepatocyte zones (PP, Mid, and PC) at 0, 3, 6, and 24 hours post-APAP (Figure 2A). Throughout the 0 to 24-hour period post-APAP, gene expression in the PP remained relatively stable. At 0, 3, and 6 hours post-APAP, genes associated with metabolism (such as Hsd17b13, Fabp1, Apoc2, Thrsp for fat metabolism; Rida, Hal, Gls2, Bhmt for fatty acid metabolism; Aldob, Pck1 for glucose metabolism) and transport (such as Alb, Hpx, Selenop, Trf, Lcn2) were prominently expressed, with a notable upregulation of inflammatory response-related genes (such as Orm1, Serpina1c, Lrg1) observed at 24 hours post-APAP (Figure 2A). In contrast, Mid-zone exhibited significant changes over time. Initially, it showed high expression of genes related to cell proliferation (such as Igfbp2), metabolism (such as Scd1, Cdo1, Ces1c, Ttr, Apoa1), and homeostasis (such as Hamp, Cps1, Rgn) at 0 hours, transitioning to stress response/cell survival (such as Hmox1, Hspa8, Atf3, Osgin1) and protein degradation/autophagy (such as Ubb, Ubc, Sqstm1) at 3 and 6 hours, and eventually shifting to cell proliferation and wound healing (such as Fgg, Fgl1, Fgb) by 24 hours post-APAP (Figure 2A). The PC showed a decrease in xenobiotic metabolism (such as Cyp3a11, Cyp2e1, Cyp1a2, Cyp2c37) and fat metabolism (such as Apoe, Akr1c6, Hpd, Oat) during early AILI (at 0, 3, 6 hours post-APAP), with a marked increase in the expression of genes related to cytoskeleton (such as Actb, Krt8, Krt18) and redox regulation (such as Prdx1, Srxn1) observed at 24 hours post-APAP (Figure 2A). These differential expression patterns across various zones and time points post-APAP highlight significant changes in Mid-zone. Notably, our analysis suggests that the Mid-zone undergoes a stress adaption during the initial phases of acute liver injury.

Figure 2.

Further analysis focuses on DEGs in Mid-zone at 6 hours post-APAP compared to 0 hour. The volcano plot revealed a notable increase in the number of genes significantly upregulated in the mid zones at 6 hours, predominantly associated with the stress response and adaptation (such as Atf3, Hmox1, Osgin1, Ddit3, Gadd45a, Atf4, Jun, Hspa1) as well as cell proliferation and apoptosis (such as Btg2, Egr1, Igfbp1, Sqstm1, Dnajb1) (Figure 2B). Among the significantly upregulated genes, Sqstm1 (Sequestosome 1) was selected for further validation. Sqstm1 encodes the p62 protein, a key regulator of autophagy and oxidative stress response.²⁰ While Sqstm1 expression was almost evenly distributed across all zones at 0 hours, it was markedly elevated in the mid-zone at 6 hours post-APAP (Figure 2C). Immunohistochemical staining further confirmed the distinct localization of p62 in the mid-zone at this time point (Figure 2D). Together, our findings indicate that Mid-zone hepatocytes undergo dynamic changes during the early phases of acute liver injury, primarily characterized by stress response and adaptation.

Further ST analysis revealed that Ki67-positive spots also show a transient reduction during the early injury (at 3 and 6 hours post-APAP) (Figure 2E), which aligns with the findings from Ki67 immunohistochemical staining. Cell cycle analysis is crucial for understanding cell proliferation, as it reviews the stages of the cell cycle that cells are in and how many cells are actively dividing.(23) In the cell cycle, the S phase is responsible for DNA synthesis and replication, while the G2M phase prepares cells for and executes mitosis.(23) Analysis of cell-cycle phase distribution, based on genes identified in previous studies,(24, 25) revealed that Mid-zone hepatocytes exhibited a transient increase in S-phase genes at 3 hours, followed by a decline at later time points (6, and 24 hours). In contrast, Mid-zone hepatocytes exhibited reduced G2/M-phase scores at 3 and 6 hours, returning to baseline levels by 24 hours (Figure 2F). This suggests that Mid-zone hepatocytes may initiate DNA synthesis, but they are unable to complete the cycle due to the environmental toxicity or cellular damage. Nuclear Autoantigenic Sperm Protein (Nasp) binds to histones and facilitate chromatin assembly during the S phase.²¹ Casein Kinase 1 Beta (Cks1b) participates in the control of G1 phase and the transition to the S phase.²² High Nasp levels indicate efforts toward DNA repair and chromatin stability, while low Cks1b levels point to a potential cell cycle arrest or a reduction in cell proliferation to manage the damage (Figure 2G). Overall, ST analysis revealed that Mid-zone hepatocytes exhibit distinct gene expression profiles and cell cycle arrest during early acute injury.

Zonal metabolism of APAP leads to stress response in Mid-zone hepatocytes

Next, we aimed to elucidate the cause for the stress response observed in the Mid-zone during early APAP. APAP is metabolized by cytochrome P450 enzymes (Cyp family) into reactive metabolites, particularly N-acetyl-p-benzoquinone imine (NAPQI), which can induce oxidative stress and damage cellular components if not promptly detoxified by glutathione (GSH) (Figure 3A). We analyzed the gene expression levels of Cyp family enzymes in hepatocyte zones (PP, Mid, and PC) at 0, 3, 6, and 24 hours post-APAP. Our analysis revealed a gradient decrease in the expression levels of most Cyp enzymes, showing a trend from high expression in PC to lower expression in PP (Figure 3B). Scatter plots of representative Cyp enzymes, such as Cyp2e1 and Cyp1a2, clearly showed a temporal and spatial expression pattern consistent with this gradient decrease from CV to PV (Figure S2A). Immunohistochemical staining of Cyp1a2 confirmed its gradient decrease in protein expression from the CV to the PV under homeostatic conditions (0 hour). However, following APAP-induced toxicity, Cyp1a2 expression declined around the CV— where necrosis was prominent—during the injury initiation phase (3–24 hours post-APAP). Consequently, the Mid-zone adjacent to necrotic regions emerged as the primary area retaining Cyp1a2 expression (Figure 3C, D). These findings suggest that the spatial redistribution of Cyp expression establishes the Mid-zone as the primary site of APAP metabolism during early AILI, thereby inducing subsequent transcriptional reprogramming (Figure 3E).

Figure 3.

To investigate this hypothesis, we administered mice with varying doses of APAP (100, 300, and 500 mg/kg) to induce different extents of liver injury. H&E staining revealed a dose-dependent increase in the size of the injured areas, with higher doses resulting in larger areas of injury (Figure S2B and S2C). Subsequently, we performed immunofluorescence staining for Chop, a protein differentially highly expressed in the Mid-zone at 6 hours post-APAP compared to 0 hour (as identified in Figure 2B), to assess the Mid-zone response. Our findings indicate that Chop expression is absent at low doses of APAP when necrosis does not occur. However, as the dose of APAP increases, the injured area expands, and Chop expression shifts toward the PV, consistently surrounding the injured area (Figure 3F and G). Together, these findings demonstrate that CV necrosis establishes the adjacent peri-necrotic region as the dominant site of APAP metabolism, contingent upon both Cyp family expression levels and APAP dosage. This spatially restricted metabolic adaptation drives subsequent region-specific transcriptional changes in the surrounding parenchyma (Figure 3H).

The Atf4-Chop axis emerges as pivotal in Mid-zone during early acute injury

To explore master regulator of stress adaptation in Mid-zone, we constructed gene regulatory networks from the ST data. We identified the top 10 regulons in each zone at 3 and 6 hours post-APAP (Figure 4A and Figure S3A). A closer examination of the transcription factors (TFs) in the Mid-zone revealed that Atf4, Fos, Nfil3, Egr1, Maff, Atf3, and Ddit3 co-activated at both time points. Atf4, Chop, and Atf3 play crucial roles in managing cellular stress responses.^23,24 Fos and Egr1 are immediate early genes that are rapidly activated in response to stimuli, regulating genes related to growth and stress responses.²⁵ Maff and Nfil3 contribute to the management of oxidative stress and metabolic processes.^26,27 The elevated activity of these TFs in the Mid-zone indicates that this region is undergoing a complex response to stress, serving as a critical area for cellular adaptation, survival, and potential necrosis during early liver injury.

Figure 4.

Among the top 10 TFs with highest activity in the Mid-zone during early AILI, Ddit3 and Atf3 were the two most highly expressed, with Atf4 ranking seventh (Figure 4B and Figure S3B). Since Ddit3 expression is often regulated by Atf4, and the Atf4-Ddit3 axis plays a critical role in stress adaptation,²⁸ we chose to focus on this pathway for further investigation. The violin plot analysis demonstrated that Atf4 and Ddit3 were prominently active in Mid-zone, particularly at 3 and 6 hours post-APAP (Figure 4C and Figure S3C). Gene regulatory networks illustrated associations between Atf4 and its target genes (such as Gdf15, Hspa8, and Ddit3) and Ddit3 with its targets (such as Hspa8, Hmox1, Osgin1, Gadd45a, and Egr1) at 3 hours post-APAP (Figure S3D). Heatmap further clearly showed that the target genes of Atf4 and Ddit3 are exclusively expressed in the Mid-zone hepatocytes at 6 hours post-APAP (Figure 4D). Many of these target genes were DEGs in Mid-zone during early AILI, underscoring the critical role of the Atf4-Ddit3 axis in orchestrating gene expression changes in this region.

From the regulatory networks, it is evident that many genes regulated by Atf4 and Chop overlap. Therefore, we conducted a GO pathway analysis to identify the pathways co-regulated by Atf4 and Chop. The results revealed the top 15 enriched pathways for genes co-regulated by Atf4 and Chop in Mid-zone at 3 and 6 hours post-APAP (Figure 4E and Figure S3E). These pathways encompass responses to unfolded proteins, stress, autophagy, and regulation of apoptotic signaling pathways. Additionally, GO pathway analysis identified the top 15 enriched pathways for up-regulated genes specifically in Mid-zone at 3 hours post-APAP compared to other zones, further highlighting pathways co-regulated by Atf4 and Chop in response to APAP (Figure S3F). The pathways co-regulated by Atf4 and Chop point to the activation of ISR. To confirm the occurrence of ISR in Mid-zone during the initiation stage of AILI, we performed immunohistochemical staining for phosphorylated eIF2α (p-eIF2α) at 0 and 3 hours post-APAP and observed increased expression of p-eIF2α in the mid-zone (Figure 4F). While the ISR is a generalized pathway integrating endoplasmic reticulum (ER) stress and other insults through eIF2α kinases, ER stress is a subset of cellular stresses that activates the unfolded protein response (UPR) via PERK/IRE1/ATF6. Their overlap occurs at PERK-eIF2α-ATF4, but ER stress uniquely engages IRE1/XBP1 and ATF6 for ER-specific repair.¹⁵ To evaluate the involvement of ER stress in Mid-zone, we further analyzed the expression levels of genes related to stress response and ER stress based on DEGs identified in Mid-zone at 0, 3, and 6 hours post-APAP treatment (Figure 4G and Figure S3G). Most of stress response-related genes are highly upregulated (Figure 4G and Figure S3G). However, despite the high expression of Atf4 and Ddit3, other ER stress-related genes, such as Eif2ak3, Atf6, and Xbp1 ²⁸ either remained unchanged or were downregulated at 3 and 6 hours compared to 0 hour post-APAP (Figure 4G and Figure S3G). This analysis highlights the unique role of the Atf4-Ddit3 axis in Mid-zone during early AILI.

To validate Mid-zone responses and transcriptional changes during early AILI, we analyzed an additional scRNA-seq dataset from AILI mice.²⁹ UMAP visualization demonstrated that hepatocytes could be clustered into three distinct zones (PP, PC, and Mid) at 3 and 6 hours post-APAP (Figures S4A and S4B). The zonal gene expression patterns were confirmed, with PC-specific genes (Glul, Cyp2e1, Cyp2a5), PP-specific genes (Alb, Cyp2f2, Sds), and Mid-zone genes (Hmox1, Atf3, Ubc) exhibiting distinct spatial distributions (Figure S4C). GO pathway analysis revealed the top 10 enriched pathways for upregulated genes in Mid-zonal hepatocytes at 3 and 6 hours post-APAP, highlighting key stress-response and cell death processes (Figures S4D and S4E). Consistent with our findings, SCENIC analysis also identified the activation of similar TF motifs across zonal regions, with distinct Ddit3 and Atf3 motifs activated in Mid-zone hepatocytes at 3 and 6 hours post-APAP (Figures S4F and S4G). These results reinforce the regulatory changes observed in our ST data, further emphasizing the unique role of mid-zonal hepatocytes in stress adaptation.

The Atf4-Ddit3 axis protects hepatocytes from liver injury

To investigate the role of Atf4-Ddit3 axis in cell fate determination, we first examined Atf4 expression in liver sections by immunohistochemical staining at 0 and 6 hours post-APAP. The results showed gradual increased expression of Atf4 in Mid-zone during early AILI (Figure 5A). Subsequently, we employed the adeno-associated virus 8 (AAV8) and thyroxine-binding globulin (TBG) promoter method to overexpress Atf4 specifically in hepatocytes (Figure 5B). Atf4 overexpression significantly reduced AILI, as evidenced by H&E staining and serum ALT levels (Figure 5C and 5D). Furthermore, immunohistochemical staining of Atf4 indicated its localization in hepatocyte nuclei around the injured area (Figure 5E). Immunofluorescence and immunohistochemical staining for Ki67 and p-eIF2α, respectively, showed that Atf4 overexpression notably decreased Ki67 expression and increased p-eIF2α expression (Figure 5F and 5G). Together, these findings suggest that elevated Atf4 expression enhances ISR, offering stress protection under conditions of reduced proliferation.

Figure 5

The Atf4-Ddit3 axis protects the liver by pausing proliferation via Btg2

Atf4 often works with Ddit3 to mediate stress response, particularly in the context of the ISR.^23,24,30 Given the low expression of Atf4 and high expression of Ddit3 in the Mid-zone, we performed Cut&Run to identify the genomic regions where Ddit3 binds during the initiation phases of AILI. This approach was used to investigate how the Atf4-Ddit3 axis regulates the proliferation of Mid-zone hepatocytes. Compared with the input control, we observed heightened Ddit3-binding signals within the chromatin domains (Figure 6A). We further overlapped 6157 genes where Ddit3 binds, as identified by Cut&Run, with 47 DEGs specifically in the Mid-zone hepatocytes, identifying 39 overlapping genes termed Ddit3-binding DEGs (Figure 6B). Integrative Genomics Viewer (IGV) plots illustrate Ddit3-binding peaks and input controls at specific genomic sites such as Btg2, Atf3, Dnajb1, and Egr1 regulatory elements (Figure 6C).

Figure 6.

Among the Ddit3-binding DEGs, we observed B-cell translocation gene 2 (Btg2), which is cell cycle inhibitor.^31–33 Moreover, Btg2 is one of the target genes that coregulated by Ddit3 and Atf4. Immunohistochemical staining of Btg2 in liver sections at 0 and 6 hours post-APAP revealed increased expression of Btg2 around the injured area in response to APAP (Figure 6D). Additionally, we investigated whether Ddit3 could upregulate Btg2 expression in Mid-zone. We overexpressed Ddit3 in the hepatocytes of wildtype C57BL/6J mice using the AAV8 method, with EGFP overexpression serving as a control (Figure 6E). Immunohistochemical staining of Btg2 in liver sections from mice overexpressing either AAV-TBG-EGFP or AAV-TBG-Ddit3 at 12 hours post-APAP indicated that Ddit3 overexpression significantly upregulated Btg2 expression post-APAP (Figure 6F). This result suggests that Btg2 is a downstream target of Ddit3.

To explore the role of Btg2 in liver injury and hepatocyte proliferation, we further overexpressed Btg2 in hepatocytes of wildtype C57BL/6J mice (Figure 6G). H&E staining and serum ALT levels indicated that Btg2 overexpression significantly reduced AILI (Figure 6H and 6I). Ki67 staining further demonstrated that Btg2 overexpression significantly decreased hepatocyte proliferation (Figure 6J). Moreover, we used the CasRx-sgRNA system³⁴ to knock down Btg2 by overexpressing either IP479-EFS-sgEGFP or IP479-EFS-sgBtg2. In contrast to Btg2 overexpression, Btg2 knockdown resulted in increased Ki67 expression in hepatocytes, suggesting enhanced hepatocyte proliferation (Figure 6K). Together, these findings illustrate Atf4-Ddit3 axis inhibits hepatocytes proliferation in Mid-zone via Btg2 during early AILI.

Discussion

Our study reveals that during the early phase of AILI, mid-zone hepatocytes undergo a transient proliferation arrest, orchestrated by a distinctive transcriptional program centered on the Atf4-Chop axis. Spatial transcriptomics and functional assays demonstrate that this adaptive response promotes survival by upregulating the cell cycle inhibitor Btg2, highlighting a trade-off between cytoprotection and proliferative capacity. Notably, zonal metabolic heterogeneity in APAP processing drives preferential activation of these stress pathways in mid-zone hepatocytes. These findings uncover a critical mechanism by which hepatocytes prioritize stress adaptation before initiating regeneration, offering new insights into the spatiotemporal regulation of liver repair (Figure 7).

Figure 7.

Our study reveals that mid-zone hepatocytes employ a protective proliferation arrest during early AILI, mediated by the Atf4-Chop axis of the integrated stress response (ISR). While the ISR shares upstream initiators with ER stress (e.g., eIF2α phosphorylation), its outcomes are context-dependent. ER stress specifically activates the unfolded protein response (UPR) through sensors inositol-requiring enzyme 1α (IRE1α), activating transcription factor 6 (ATF6), and protein kinase RNA-like ER kinase (PERK),³⁵ with genetic studies demonstrating their critical roles in AILI – knockout of IRE1α, X-box binding protein 1 (XBP1), or Chop consistently attenuates liver damage, confirming the UPR’s contribution to hepatotoxicity.^19,36–38 Unlike classical ER stress, we find that mid-zone hepatocytes leverage the Atf4-Chop axis to transiently halt proliferation via Btg2, favoring survival. This aligns with emerging evidence that Chop can paradoxically support adaptation in mitochondrial stress,^30,39 suggesting that its role in fine-turning of ISR in mammals.

The antiproliferative activity of Btg2 has been studied through an integrated network of transcriptional and post-transcriptional cell cycle regulatory mechanisms. A study reveals that Btg2 functions as a molecular bridge between poly(A)-binding protein cytoplasmic 1 (PABPC1) and the CCR4-NOT deadenylase complex subunit CNOT7 (CAF1), facilitating accelerated degradation of cell cycle-related transcripts through enhanced poly(A) tail removal.³¹ At the transcriptional level, Btg2 exerts specific control over G2/M progression by disrupting the positive feedback loop between cyclin B1 and its transcriptional activator FOXM1 (forkhead box protein M1), thereby suppressing cyclin B1 expression and inducing cell cycle arrest.³² Furthermore, Btg2 demonstrates broader cell cycle inhibitory capacity through its interactions with cyclin-dependent kinases (CDKs) during G1/S transition and its ability to modulate the tumor suppressor p53 (TP53).³³ In the context of AILI, the stress-responsive Atf4-Chop pathway induces Btg2 expression in mid-zonal hepatocytes, where it may coordinate a comprehensive proliferation arrest through these complementary mechanisms. This multilayered regulatory strategy enables hepatocytes to temporarily suspend cell division and redirect resources toward cellular repair and stress adaptation during the acute phase of toxic injury.

A key limitation of this study is the scarcity of early-phase AILI human samples, which currently precludes definitive validation of the clinical relevance of these zonal adaptations. To address this gap, we performed a preliminary analysis of published single-cell RNA sequencing data from APAP-overdose patients.²⁹ Intriguingly, in one of two analyzed patients, mid-zone hepatocytes exhibited transcriptional signatures remarkably consistent with our murine findings, including: (1) upregulation of Atf4-Chop pathways, and (2) downregulation of cell proliferation genes. While the small sample size (n=2) prevents definitive conclusions, these preliminary observations suggest potential conservation of stress-responsive mechanisms between murine and human mid-zone hepatocytes during AILI. Further studies with larger clinical cohorts will be essential to verify these findings and establish their translational significance.

In summary, our study uncovers a spatially coordinated stress adaptation mechanism in mid-zone hepatocytes during early AILI, where the Atf4-Chop axis transiently suppresses proliferation via Btg2 upregulation. By elucidating how hepatocytes prioritize survival before initiating repair, our work provides a framework for understanding the dynamic interplay between stress adaptation and regeneration in tissues.

Methods and materials

Detailed methods can be found in additional files.

Data and code availability

Cut&run data are accessible (GSE272565). ST data are accessible (GSE272564). This paper does not report original code.

Acknowledgements

We thank Bin Qi (Yunnan University) for suggestions and discussion. We thank Dr. Yin Hao (Wuhan University) for providing us the pHelper and pAAV2/8 plasmids. We thank Shalev Itzkovitz (Weizmann Institute of Science) for providing us the smFISH protocol. We thank Hui Yang (Institute of Neuroscience, SBS, CAS) for providing us the plasmids related to CasRx system. We thank Yonglong Wei (Yunnan University) for helping in quantification of spatial distribution. This work was supported by Yunnan Provincial Science and Technology Department (C619300A086 to Z.S.), National Natural Science Foundation of China (32170662 to C.P.), and Yunnan Fundamental Research Project (202401AS070131 to C.P.).

Additional information

Author Contributions

Y.Y.Z. performed the experiments, analyzed the data, and wrote the methods and figure legends. C.X.D. initially analyzed the sequencing data, while B.C. continued the sequencing data analysis, performed the experiments, wrote the methods and figure legends. J.H. prepared the ST samples. Y.N.L. performed the experiments. C.P. supervised the ST data analysis by C.X.D., participated in the initial study design, and revised the manuscript. Z.S. initiated, organized, and designed the study, and wrote the manuscript.

Additional files

Supplementary figures

Supplementary methods