bioRxiv Science⌕ Search

bioRxiv · 10.1101/2025.11.27.690787

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

Abstract

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.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Neckermann, L., Erdoesi, P., Dropmann, A., Othman, A., Weinert, J., Albin, J. E., Wolf, S. D., begher-Tibbe, B., von Recklinghausen, I., Caccamo, T., Ebert, M. P., Bode, J. G., Hengstler, J., Dooley, S., Hammad, S.. 2025-12-01. Immunoglobulin G binding as a quantitative marker of hepatocellular death across acute and chronic liver injury. https://doi.org/10.1101/2025.11.27.690787

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Not all TOP RNAs are created equal: 3'UTR length and TSS selection predict the translational regulation of LARP1-bound mRNAs in CD4+ T cells

Naive T cells are poised for activation and contain a pool of translationally repressed ribosomal protein (RP) mRNA prepared to induce ribosome biogenesis to support protein synthesis, cell growth and proliferation. RP mRNA are the prototypical members of a class of transcripts initiating at cytosine followed by a CU rich element called terminal oligo pyrimidine (TOP) RNAs. TOP RNAs are regulated by an RNA binding protein LARP1, which promotes transcript stabilisation and translational repression. We investigated LARP1 function in T cell activation by generating cross-linking immunoprecipitation (CLIP) datasets detailing the LARP1-RNA interactions in naive and activated CD4+ T cells and identifying novel TOP RNAs. TOP RNAs identified by this analysis were functionally diverse. RP mRNAs were typified by high stability, and translational repression in naive T cells followed by MTORC1-dependent translation increases following T cell activation. However, other TOP RNAs varied in these aspects of their regulation. Notably, TOP RNAs with longer 3'UTRs had a relaxed dependency on LARP1 for stability and a reduced dependency on MTORC1 for their translation. Transcription start site heterogeneity also impacted TOP RNA regulation by generating a mixture of transcript isoforms with different TOP motif lengths. Longer terminal oligo pyrimidine stretches were associated with a greater dependency on MTORC1 for translation. Differential regulation of TOP RNAs may allow tuneable translational responses to MTORC1 and indicates potential roles for LARP1 beyond translation regulation and stability.

cell biology↗

Sex-specific metabolic regulation by the Drosophila RNA-binding protein Nab2

Conserved RNA binding proteins (RBPs) regulate key steps of gene expression including mRNA processing, export, localization, stability and translation. Human ZC3H14 is a conserved RBP that regulates pre-mRNA processing in neurons and loss of ZC3H14 leads to neurological defects. Studies of Nab2, the Drosophila orthologue of ZC3H14, have identified potential target RNAs involved in metabolism, suggesting Nab2 may influence neurometabolic circuitry. Here, we show a female-specific increase in dilp2 and dilp5 mRNA levels. The dilps encode insulin-like peptides that signal from the brain insulin producing cells (IPCs) to peripheral tissues. Nab2null females have enlarged lipid droplets in the fat body, a tissue analogous to human adipose tissue and liver. Notably, neuronal depletion of Nab2 increases lipid droplet size while neuronal expression of Nab2 in Nab2null female rescues this phenotype supporting a role for Nab2 in a neuronal circuit that regulates dilp levels. Furthermore, depletion of dilp2 or dilp5 from IPCs rescues the enlarged lipid droplet phenotype in Nab2null females indicating that elevated dilp2/dilp5 contributes to enlarged lipid droplets. Together, these data support a female-specific role for Nab2 in brain neurons to support insulin signaling and fat storage, expanding the known functions of RBPs linking neuronal function and metabolic homeostasis.

cell biology↗

Deep generative embeddings of gene expression and splicing reposition the interpretation of single-cell transcriptomic signatures

Single-cell transcriptomic analysis predominantly derives cell identity from gene expression analysis, while alternative splicing is processed separately despite its fundamental role for cell homeostasis. To overcome the limits of separate investigations, we developed a probabilistic deep learning framework, Crecerelle, enabling resolution of the contributions of gene expression and alternative splicing in each cell. Crecerelle learns cell embeddings from gene expressions and alternative splicing isoforms, to decipher their mutually dependent impact on the functional characterisation of cells in a data-driven manner, exemplified for the Tabula Muris dataset. This is enabled through a zero-and-N-inflated Dirichlet-Multinomial for a variational autoencoder that learns cell embeddings solely from splicing profiles, as well as a bi-modal variational autoencoder with a relevance-weighted mixture-of-experts variational posterior to consolidate the modality-specific contribution at single-cell level. Crecerelle reveals cell-type-specific isoform markers as well as subpopulations with unique isoforms and uncovers regulatory and disease-associated pathways not detected by gene expression analyses alone. This scalable and interpretable framework thus allows a more holistic study of transcriptomic regulation and will open a route to modality-relevance-weighted investigations across single-cell multiomics datasets and their influence on cellular homeostasis, tissue development and disease phenotypes.

cell biology↗