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Functional editing of the OTC locus by targeted integration with phenotype correction and restoration of endogenous expression patterns.

Here, we report highly efficient functional repair of the ornithine transcarbamylase (OTC) locus in mutant mouse and human hepatocytes in vivo using a dual adeno-associated virus system delivering CRISPR-Cas9 editing reagents and a promoterless donor for targeted integration. The approach was mutation agnostic and targeted intronic sequences to prevent inadvertent inactivation of hypomorphic alleles. Notably, in a murine model, we corrected the metabolic defect and simultaneously achieved liver-wide restoration of physiological metabolic zonation of Otc expression by capturing native cis-acting regulatory elements. The effectiveness of this approach was confirmed using a universally configured therapeutic cassette in patient-derived primary human hepatocytes in vivo. These data provide a powerful template to guide further optimization of this approach and, given the high editing efficacy required for phenotypic effect in OTC deficiency, have broader relevance to other liver disease phenotypes.

Animals

Loss of the Mechanistic Target of Rapamycin Complex 1 Causes a Lethal Alpha-1 Antitrypsin Deficiency-Associated Liver Disease.

BACKGROUND & AIMS: SERPINA1 mutations cause retention of the otherwise secreted alpha-1 antitrypsin and lead to the proteotoxic alpha-1 antitrypsin deficiency-related liver disease. As mechanistic target of rapamycin is a key coordinator of proteostasis, we studied its role in alpha-1 antitrypsin deficiency-related liver disease. METHODS: PiZ mice overexpressing the characteristic SERPINA1 mutation were mated with rodents harboring a hepatocyte specific-ablation of the interaction partners regulatory-associated protein of mechanistic target of rapamycin or rapamycin-insensitive companion of mammalian target of rapamycin, corresponding to mechanistic target of rapamycin complexes 1 or 2, or with mice lacking mechanistic target of rapamycin. Serum proteomics, liver bulk proteomics, spatial proteomics, and metabolomics were applied to characterize molecular and metabolic alterations. RESULTS: At 2 months of age, PiZ-mTORΔhep and PiZ-RaptorΔhep but not PiZ-RictorΔhep mice showed signs of increased liver injury and mortality despite diminished hepatic alpha-1 antitrypsin accumulation. PiZ-RaptorΔhep animals displayed increased levels of the proapoptotic protein C/EBP homologous protein, but C/EBP homologous protein ablation did not rescue the phenotype. Serum proteomics revealed no signs of advanced synthetic liver failure but immature hepatocellular products. Liver bulk proteomics and small metabolite measurement demonstrated a metabolic reprogramming of PiZ-RaptorΔhep mice. Spatial proteomics revealed alterations in liver zonation with increased ammonia levels as the likely cause of death in PiZ-RaptorΔhep animals. CONCLUSIONS: In summary, in alpha-1 antitrypsin deficiency-related proteotoxic liver injury, regulatory-associated protein of mechanistic target of rapamycin preserves a liver zonation, thereby protecting from lethal metabolic dysregulation.

Animals

Environmental Gradients as a Dominant Force in the Macroevolution of a Host-Associated Marine Bacterium.

Natural selection is imposed by both abiotic environmental filtering and biotic interactions, yet their relative roles in shaping the deep phylogeny of widespread, generalist host-associated bacteria remain unclear. Here, we integrate large-scale phylogenomics, environmental sequencing, functional genomics, and global metagenomic analysis to demonstrate that tidal zonation overrides host association as the dominant macroevolutionary force structuring the marine bacterial genus Ruegeria. Analysis of 533 genomes and 74 global coastal metagenomes reveals that the intertidal-subtidal boundary structures the deepest phylogenetic splits, driving the repeated evolution of distinct ecotypes through independent zonation transitions across global coastlines. These ecotypes possess divergent genomic toolkits: intertidal strains are enriched for genes coding for stress resistance and anaerobic metabolism, whereas subtidal strains specialize in high-affinity nutrient scavenging. Our findings establish that predictable physicochemical gradients act as filters that generate foundational diversity from which specialized host symbionts subsequently emerge, reframing how environmental gradients shape microbial evolution at the eco-evolutionary interface.

Journal Article

Toward AI Virtual Cells for Hepatology: Representation, Generation, Dynamics, and Intervention in Single-Cell Models.

``Single-cell and spatial atlases describe the healthy and diseased liver at high resolution, including lobular hepatocyte zonation, fibrotic macrophage-stellate niches, cholangiocyte reactions, immune remodeling, and hepatocellular carcinoma ecosystems. These maps show where cell states occur but do not, by themselves, predict whether liver injury will progress or how the liver will respond to an untested drug, toxicant, or genetic perturbation. In this review, we organize current approaches toward an AI Virtual Cell (AIVC) for the liver into three complementary modeling routes. Generative models represent cell states, dynamics and transport models infer state transitions, and pretrained or foundation models test whether learned representations transfer across donors, etiologies, disease stages, and platforms. Perturbation-response prediction serves as a cross-cutting assessment of whether these layers can predict responses to untested genetic, chemical, inflammatory, or metabolic interventions. Available evidence can be categorized as direct liver validation, liver-included benchmarks, general single-cell evidence, and conceptual applications. Published models demonstrate individual components, including atlas integration, inferred trajectories, transferable representations, and retrospective response programs. However, these models do not constitute a prospectively validated liver simulator. At minimum, evaluation should include donor-, etiology-, stage-, platform-, and perturbation-level hold-outs. Model performance should be reported using response direction, recovery of differentially expressed genes and rare states, and calibrated uncertainty. Claims about tissue- or function-level prediction additionally require independent spatial, histologic, metabolic, and functional readouts. Near-term use should prioritize experiment selection and hypothesis generation, whereas clinical decision support remains a longer-term objective.

AI Virtual Cell

Hepatocyte dedifferentiation in 2D culture reveals extensive transcriptomic and proteomic rewiring.

BACKGROUND: Primary hepatocytes are commonly used in vitro to model liver metabolism, but prolonged culturing results in dedifferentiation and potentially limits the applicability of this model. METHODS: We characterized the transcriptome and proteome of full liver and primary hepatocytes as either freshly isolated cells or after 24 hours of 2D-culturing. RESULTS: We found that 2D-culturing for 24 hours changes more than 10,000 genes and 3000 proteins compared with freshly isolated cells, accompanied by a decrease in transcriptional heterogeneity and a loss of zonal markers. Moreover, there were changes in proteins associated with the extracellular matrix, in mitochondrial and ribosomal protein abundances, as well as an increase in the abundance of acute-phase response proteins. CONCLUSION: Collectively, primary mouse hepatocytes in culture rewire the transcriptome and proteome, which may affect the utility of this model to study physiological and molecular mechanisms related to the liver. We developed the Shiny app "Hepamorphosis" (https://cbmr.ku.dk/research/resources/shiny-apps/), which allows users to explore RNA/protein correlations, zonation profiles, and cell-type-specific transcription in full liver and cultured hepatocytes.

Hepatocytes