Biology subjects

Hengstler, J.

Publications and source records attributed to Hengstler, J..

8 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

Electrophysiological resting-state signatures link polygenic scores to general intelligence

Intelligence is associated with important life outcomes. Behavioral, genetic, structural, and functional brain correlates of intelligence have been studied for decades, but questions remain as to how genetics are related to trait expression and what intermediary role brain properties play. This study investigated these mediations in a representative sample of 434 individuals, comprising young and older adults. Polygenic scores (PGS) for intelligence were calculated. Resting-state EEG recordings were analyzed using graph theory quantifying functional connectivity across different frequencies. We tested whether global and local graph metrics like efficiency and clustering mediated the association between PGS and intelligence. PGS significantly predicted variance in intelligence and were related to frequency-specific graph metrics in areas predominantly located in parieto-frontal regions, which in turn were associated with intelligence. These findings, which are based on the first study linking PGS to intelligence using EEG-derived graph metrics, advance our understanding of the neurogenetics of intelligence.

neuroscience↗

bioRxiv2023

RAB18 confers protection to lipid droplets from lysolipophagy and counters cellular steatosis

Lipid droplet (LD) enlargement is the most conspicuous cellular phenotype of steatotic liver diseases such as NAFLD and NASH. The small GTPase RAB18 localizes to lipid droplets yet its effects on LD dynamics are unknown. We show that RAB18 localizes to LDs dynamically via the acylation cycle in an activity dependent manner. Removal of RAB18 from LDs through acylation cycle inhibition of RNAi-mediated downregulation leads to an increase in LD size, that can be prevented by inhibition of autophagy. We propose a model where RAB18 on LDs decreases the susceptibility of LDs to autophagy by lysosomes, allowing them to exist longer in cells and enabling an even distribution of exogenous lipid load. In the absence of RAB18, fewer LDs survive autophagic removal, and enlarge disproportionately as they absorb the incumbent exogenous lipid load on cells - leading to cellular steatosis. Inhibition of autophagy prevented cellular steatosis in primary human hepatocytes. Finally, mice treated with the autophagy inhibitor chloroquine were resistant to the development of liver steatosis when on a steatogenic diet. The modulation of RAB18 activity and autophagy inhibition represents a promising approach to prevent steatotic liver disease in the clinical setting. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/531838v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@57d8f8org.highwire.dtl.DTLVardef@165ad0aorg.highwire.dtl.DTLVardef@43964corg.highwire.dtl.DTLVardef@140746f_HPS_FORMAT_FIGEXP M_FIG C_FIG One line summaryRAB18 prevents lipid droplet autophagy to distribute lipid load in cells and prevent steatosis.

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↗

bioRxiv2021

Sleep-dependent upscaled excitability and saturated neuroplasticity in the human brain: From brain physiology to cognition

Sleep strongly affects synaptic strength, making it critical for cognition, especially learning, and memory formation. Whether and how sleep deprivation modulates human brain physiology and cognition is not well understood. Here we examined how overnight sleep deprivation vs sufficient sleep affects (a) cortical excitability, as measured by transcranial magnetic stimulation (TMS), (b) inducibility of LTP-and-LTD-like plasticity via transcranial direct current stimulation (tDCS), and (c) learning, memory and attention. The results suggest that sleep deprivation upscales cortical excitability due to enhanced glutamate-related cortical facilitation and decreased and/or reversed GABAergic cortical inhibition. Furthermore, tDCS-induced LTP-like plasticity abolishes while LTD-like plasticity converts to excitatory LTP-like plasticity under sleep deprivation. This is associated with increased EEG theta activity, which is related to sleep pressure. Finally, we show that learning and memory formation, behavioral counterparts of plasticity, and working memory and attention, which rely on cortical excitability, are impaired during sleep deprivation. Our data suggest that upscaled brain excitability, and altered plasticity, due to sleep deprivation, are associated with impaired cognitive performance.

neuroscience↗

bioRxiv2018

CRUP: A comprehensive framework to predict condition-specific regulatory units

We present the software CRUP (Condition-specific Regulatory Units Prediction) to infer from epigenetic marks a list of regulatory units consisting of dynamically changing enhancers with their target genes. The workflow consists of a novel pre-trained enhancer predictor that can be reliably applied across cell lines and species, solely based on histone modification ChIP-seq data. Enhancers are subsequently assigned to different conditions and correlated with gene expression to derive regulatory units. We thoroughly test and then apply CRUP to a rheumatoid arthritis model, identifying enhancer-gene pairs comprising known disease genes as well as new candidate genes.\n\nAvailabilityhttps://github.com/VerenaHeinrich/CRUP

bioinformatics↗

bioRxiv2018

Partially methylated domains are hallmarks of a cell specific epigenome topology

BackgroundPartially methylated domains, PMDs, are extended regions in the genome exhibiting a reduced average DNA-methylation level. PMDs cover gene-poor and transcriptionally inactive regions and tend to be heterochromatic. Here, we present a first comprehensive comparative analysis of PMDs across more than 190 WGBS methylomes of human and mouse cells providing a deep insight into structural and functional features associated with PMDs.\n\nResultsPMDs are ubiquitous signatures covering up to 75% of the genome in human and mouse cells irrespective of their tissue or cell origin. Additionally, each cell type comes with a distinct set of specific PMDs, and genes expressed in such PMDs show a strong cell type effect. Demethylation strength varies in PMDs with a tendency towards a more pronounced effect in differentiating and replicating cells. The strongest demethylation is observed in highly proliferating and immortal cancer cell lines. A decrease of DNA-methylation within PMDs tends to be linked to an increase in heterochromatic histone marks and a decrease of gene expressions. Characteristic combinations of heterochromatic signatures in PMDs are linked to domains of early, middle and late DNA-replication.\n\nConclusionPMDs are prominent signatures of long-range epigenomic organization. Integrative analysis identifies PMDs as important general, lineage- and cell-type specific topological features. PMD changes are hallmarks of cell differentiation. Demethylation of PMDs combined with increased heterochromatic marks is a feature linked to enhanced cell proliferation. In combination with broad histone marks PMDs demarcate distinct domains of late DNA-replication.

bioinformatics↗