Biology subjects

Erdoesi, P.

Publications and source records attributed to Erdoesi, P..

4 recordsLinked to original sources

bioRxiv2025

Immunoglobulin G binding as a quantitative marker of hepatocellular death across acute and chronic liver injury

Background & AimsAccurate detection of hepatocellular death is fundamental for understanding liver injury, intoxication, regeneration, and fibrosis. Conventional markers, such as serum transaminases and histopathological scoring, suffer from limited temporal resolution, high variability, and observer dependence. We evaluated immunoglobulin G (IgG) binding as a quantitative and spatially resolved marker of hepatocyte death in acute and chronic liver injury models. MethodsMale C57BL/6 mice were subjected to acute carbon tetrachloride (CCl) intoxication (1600 mg/kg, single dose), dose-escalation (0-800 mg/kg), and chronic injury paradigms including Western diet (WD), WD+CCl, and Mdr2-/- mice with or without a single CCl challenge. The serum ALT and AST levels were measured. Liver sections were stained with IgG, Hematoxylin and Eosin (H&E), bromodeoxyuridine (BrdU), glutamine synthetase (GS), CD26, and alpha-smooth muscle actin (Acta2). Spatial and integrative transcriptomic analyses were performed to characterize the IgG hepatocyte dead regions. ResultsHepatocellular IgG labeling emerged as early as 6h post-CCl, peaked at 72-96h, and declined during regeneration. IgG-positive areas correlated strongly with Ishak necroinflammatory score (r=0.70) and serum transaminase levels (p=0.74-0.85), surpassing both in Receiver Operating Characteristic (ROC) analyses (AUC=0.92-0.95). IgG bound to both apoptotic (TUNEL) and necrotic (TUNEL-) hepatocytes. In chronic liver injury models, IgG deposition was localized to the injury zones and correlated with ALT/AST, irrespective of etiology. Multiplex imaging revealed IgG-positive necrotic cores surrounded by proliferating hepatocytes and Acta2+ myofibroblasts. Spatial transcriptomics identified immune cell enrichment, Fc{gamma}R-mediated signaling, phagocytosis, and vascular remodeling within the IgG-marked regions. ConclusionsIgG immunostaining provides a robust, quantitative, and pathologist-independent readout of hepatocellular death, which scales with injury severity, delineates necrotic zones, and reveals immune-active microenvironments. These findings establish IgG-based detection as a versatile, high-resolution tool for assessing liver injury, regeneration, and fibrosis. Conflict of Interest declarationThe authors declare that they have no affiliations with or involvement in any organization or entity with any financial interest in the subject matter or materials discussed in this manuscript. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/690787v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1d9b05eorg.highwire.dtl.DTLVardef@ca2ad8org.highwire.dtl.DTLVardef@c2d384org.highwire.dtl.DTLVardef@cca46d_HPS_FORMAT_FIGEXP M_FIG C_FIG Liver injury induced by toxins, dietary stress, or genetic knockout provokes chemokine release (i.e. CXCL1, CXCL2, and CCL3) and recruitment of immune cells, including T cells, NK cells (NKs), and dendritic cells (DCs). Activated immune cells secrete IgG, which binds to damaged hepatocytes, leading to IgG deposition and opsonization. Opsonized hepatocytes expose "eat me" signals, promoting their phagocytic clearance and contributing to the resolution of liver injury and restoration of hepatic homeostasis.

cell biology↗

bioRxiv2025

The interplay between biomechanics and cell kinetics explains the spatial pattern in liver fibrosis

The formation of liver fibrosis patterns, characterized by excess extracellular matrix (ECM), is a complex process that is difficult to investigate experimentally. To complement experimental approaches, we developed a digital twin (DT) model to simulate the pattern formation of septal and biliary fibrosis, the two common forms of liver fibrosis. This model is based on iterative calibration with experiments from animal models treated with the hepatotoxic substance CCl4 (septal form) and Abcb4-knockout mice (biliary form). Septal fibrosis is characterized by ECM accumulation along the connective line between the central veins of neighboring liver lobules, while biliary fibrosis is marked by a scattered ECM pattern within the portal fields. This mechanistic DT model includes the components of hepatocytes (Heps{spadesuit}), hepatic stellate cells (HSCs), macrophages (Mphs), bile duct (BD) cells, collagen fibers secreted by activated HSCs, blood vessels, and cell-cell communication. It allows for the integration and simultaneous modulation of multiple hypothesized mechanisms underlying fibrotic wall formation. The model simulates the formation of liver fibrosis pattern and demonstrates that ECM distribution results from the pattern of cell death zones and biomechanical compression due to cell proliferation. "Healthy" Heps proliferate to compensate for cell loss. In septal fibrosis, where the cell death zones are several cells thick, the proliferating Heps surrounding a zone mechanically compress the deposited collagen network. After a transient phase of collagen scattered between/around Heps, the ECM eventually adopts a sharp, "wall"-like structure. Whereas, in biliary fibrosis, the pattern of cell death is more scattered, leading to a corresponding scattered ECM pattern. In this case, a pattern of scattered distributed collagen forms without transitioning to a sharp wall. Notably, the failure of fibrotic wall formation in endothelial cell-specific GATA4LSEC-KO mice, due to the disrupted pattern of CYP2E1-expressing Heps, validates our DT model. In conclusion, the DT model provided a deeper understanding of liver fibrosis pattern formation. It enabled comparison between simulated outcomes of hypothesized mechanisms and experimental data. Additionally, it guided the design of validation experiments and enabled the identification of optimal strategies for drug testing and extrapolation to humans.

systems biology↗

bioRxiv2025

CD271 sorting for improved liver cell isolation: Semiautomated and simultaneous preparation of parenchymal and non-parenchymal cells from mouse and human livers

BackgroundA detailed understanding of the dynamic fate changes of hepatocytes, hepatic stellate cells (HSC), Kupffer cells (KC), and liver sinusoidal endothelial cells (LSEC) is critical for studying liver (patho)physiology during disease progression. Current isolation methods often focus on single cell types, limiting utility in comprehensive research. AimTo develop a novel, semi-automated protocol for the simultaneous isolation of hepatocytes and non-parenchymal cells (NPCs), including HSC, KC, and LSEC, from mouse and human, with high yield, purity, and viability from healthy and diseased livers. MethodThe protocol employs a two-step EGTA and collagenase II perfusion for tissue digestion. Hepatocytes were isolated by low-speed centrifugation and a Percoll gradient. Subsequently, magnetic-activated cell separation, using CD271 as a selective surface marker for HSC, CD11b for KC and CD146 for LSEC) was performed. Validation was achieved with immunofluorescence staining, flow cytometry, RT-PCR, and UV fluorescence, whereby yield, purity, and viability were assessed. ResultsWith our method, yield of hepatocytes, HSC, KC, and LSEC, is 33.4{+/-}5.5x10, 5.2{+/-}6.3x10, 12.4{+/-}4.8x10 and 18.2{+/-}8.9x10 cells per healthy mouse liver, respectively, with cell viabilities exceeding 89%, and purity surpassing 90%. CD271 was validated as an effective marker for purifying HSC in healthy and diseased human (n=4-6) and mouse livers. Compared to microfluidic and organ-on-a-chip approaches, with our protocol, we achieve higher yield and purity values while enabling the simultaneous isolation of multiple cell types from a single sample. ConclusionOur semi-automated protocol offers a scalable, reliable, and versatile solution for isolating main liver cell types with high yield, purity, and viability from both healthy and diseased tissues, advancing liver research and facilitating downstream investigations. Impact and implicationsO_LIBroad applicability: The CD271-based method efficiently isolates key liver cell types (Hepatocyte, HSC, KC, LSEC) simultaneously. C_LIO_LIVersatility in disease models: Effective for studying healthy, fibrotic, and damaged liver tissues. C_LIO_LIRobust across variability: Works reliably across different mouse strains, age groups, and conditions. C_LIO_LIHuman research potential: Scalable for high-purity isolation from human liver tissue, enabling translational studies. C_LIO_LIHigh-quality results: Ensures >85% viability and >90% purity, supporting reproducible liver research applications. C_LI

cell biology↗

bioRxiv2022

Repeated toxic injuries of murine liver are tolerated through microsteatosis and mild inflammation

The liver has a remarkable capacity to regenerate and thus compensates for repeated injuries through toxic chemicals, drugs, alcohol or malnutrition for decades. However, largely unknown is how and when alterations in the liver occur due to tolerable damaging insults. To that end, we induced repeated liver injuries over ten weeks in a mouse model injecting carbon tetrachloride (CCl4) twice a week. We lost 10% of the study animals within the first six weeks, which was accompanied by a steady deposition of extracellular matrix (ECM) regardless of metabolic activity of the liver. From week six onwards, all mice survived, and in these mice ECM deposition was rather reduced, suggesting ECM remodeling as a liver response contributing to better coping with repeated injuries. The data of time-resolved paired transcriptome and proteome profiling of 18 mice was subjected to multi-level network inference, using Knowledge guided Multi-Omics Network inference (KiMONo), identified multi-level key markers exclusively associated with the injury-tolerant liver response. Interestingly, pathways of cancer and inflammation were lighting up and were validated using independent data sets compiled of 1034 samples from publicly available human cohorts. A yet undescribed link to lipid metabolism in this damage-tolerant phase was identified. Immunostaining revealed an unexpected accumulation of small lipid droplets (microvesicular steatosis) in parallel to a recovery of catabolic processes of the liver to pre-injury levels. Further, mild inflammation was experimentally validated. Taken together, we identified week six as a critical time point to switch the liver response program from an acute response that fosters ECM accumulation to a tolerant "survival" phase with pronounced deposition of small lipid droplets in hepatocytes potentially protecting against the repetitive injury with toxic chemicals. Our data suggest that microsteatosis formation plus a mild inflammatory state represent biomarkers and probably functional liver requirements to resist chronic damage. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/476054v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@11ecc7aorg.highwire.dtl.DTLVardef@1027df5org.highwire.dtl.DTLVardef@9ba0f7org.highwire.dtl.DTLVardef@164f80a_HPS_FORMAT_FIGEXP M_FIG C_FIG The datasets generated via transcriptomics, proteomics as well as blood, histopathological and biochemical analysis were analyzed in an independent and integrative manner. The independent analysis was performed via state-of-the-art statistical approaches i.e. differential and consistently regulated genes and proteins. Combining the results identified three fibrosis phases. Using the KiMONo algorithm, a fibrosis specific multi-omic network was inferred. Within this network we identified several nodes connecting phase III specific features forming 13 distinct multi-omic modules suggesting a tolerance scheme. Some of these modules were experimentally validated and compared to 11 independent human studies of various liver diseases.

systems biology↗