Biology subjects

Mann, M.

Publications and source records attributed to Mann, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Spatiotemporal multi-omics atlas of the aging neuromuscular junction

The demographic shift toward a global aging population, coupled with rising prevalence of neurodegenerative diseases, poses major public health challenges. Aging is the primary risk factor for most neurodegenerative conditions, making the elucidation of its molecular mechanisms critical for developing effective interventions. Dysfunction of the neuromuscular junction (NMJ), the specialized synapse essential for motor function, is an early hallmark of aging and several neurodegenerative disorders, yet its molecular determinants remain incompletely understood. To shed light on potential common underlying mechanisms, we performed a spatiotemporal multi-omics analysis of the murine NMJ during aging, uncovering several genes showing decoupling between transcript and protein trajectories that may drive the related progressive motor decline. NMJs of soleus (SOL) and extensor digitorum longus (EDL) muscles, differing in fiber composition and vulnerability to aging and disease, displayed distinct spatiotemporal dynamics: fast-twitch EDL, more susceptible to degeneration, exhibited stronger mRNA-protein decoupling than aged slow-twitch SOL or younger SOL and EDL muscles. Elevated expression of miRNAs and RNA-binding proteins in aged EDL highlights the key role of post-transcriptional regulation in NMJ aging. This study provides new insights into the physiopathology of neuromuscular aging and offers a resource for investigating mechanisms shared between aging and neurodegenerative diseases. Additionally, it opens avenues for AI-driven discovery of drug targets and early biomarkers, potentially accelerating the development of therapeutic strategies.

neuroscience↗

bioRxiv2025

Cysteine availability tunes ubiquitin signaling via inverse stability of LRRC58 E3 ligase and its substrate CDO1

Cellular responses to amino acid fluctuations often hinge on ubiquitin-mediated control of metabolic enzymes, yet the underlying E3 ligase pathways remain incompletely defined. Using quantitative proteomics and active cullin-RING ligase (CRL) profiling, we identify LRRC58 as a cysteine-responsive substrate receptor whose stability increases sharply under cysteine starvation. Proteomics reveals an inverse relationship between LRRC58 and the metabolic enzyme cysteine dioxygenase 1 (CDO1), suggesting a cysteine-linked regulatory axis. Biochemical reconstitution and cryo-EM structures show that LRRC58 forms an active CUL2-or CUL5-based CRL that selectively positions CDO1 for ubiquitylation at Lys8. By contrast, targeted protein degradation via the VHL-based CRL is achieved by recruitment of a distinct surface of CDO1, and more promiscuous ubiquitylation independent of Lys8. Together, our proteomics-guided discovery pipeline, cellular stability studies, and structural analyses uncover a metabolically-tuned LRRC58-CDO1 pathway that links cysteine availability to selective proteasomal turnover, reveals principles of metabolite-regulated CRL activity, and showcases mechanisms distinguishing endogenous and targeted protein degradation.

biochemistry↗

bioRxiv2025

Multi-cohort, cross-species urinary proteomics reveals signatures of LRRK2 dysfunction in Parkinsons disease

Pathogenic mutations in Leucine-rich repeat kinase 2 (LRRK2) are the predominant genetic cause of Parkinsons disease (PD) and often increase kinase activity, making LRRK2 inhibitors promising treatment options. Although LRRK2 kinase inhibitors are advancing clinically, non-invasive readouts of LRRK2-linked pathway modulation remain limited. Profiling urinary proteomes from 1,215 individuals across three cohorts and integrating whole-genome sequencing from >500 participants to map genotype-proteome associations, we identified 177 urinary proteins associated with pathogenic LRRK2, enriched for lysosomal/glycosphingolipid, immune, and membrane-trafficking pathways. Machine learning narrowed the features to a cohort-agnostic 30-protein panel that classified G2019S carriers with a mean ROC AUC of 0.91 across independent tests. To evaluate translation, we performed multi-organ and urinary proteomics in rat gain- and loss-of-function models (BAC-LRRK2G2019S and Lrrk2KO) and after Lrrk2 inhibition (MLi-2 and PF-475), revealing tissue-specific responses--strongest in kidney--and cross-species overlap, including 24 brain proteins detectable in human urine. Rat-derived perturbations predicted LRRK2 mutation status in patients (AUC 0.75) and reversed with Lrrk2 inhibition, supporting their pharmacodynamic utility. Together, our findings establish urine as a scalable, non-invasive matrix that captures systemic and brain-relevant consequences of LRRK2 dysfunction and nominate candidate pharmacodynamic markers set to support LRRK2-directed trials.

systems biology↗

bioRxiv2025

MCUR1-CCDC90B complex is a conserved regulator of metabolic homeostasis

The mitochondrial calcium uniporter regulator 1 (MCUR1) is an evolutionarily conserved protein of the inner mitochondrial membrane1, yet its physiological role has remained elusive. Although initially proposed to function as a subunit of the mitochondrial calcium uniporter complex (MCUC)2-4, emerging evidence suggests that MCUR1 has a broader functional spectrum5-7. Here, we identify a biallelic loss-of-function MCUR1 variant (c.802C>T; p.R268X) in a patient with a progressive neurological phenotype. This mutation leads to loss of MCUR1 protein and exerts a dominant-negative effect on its paralog, CCDC90B. We show that MCUR1 and CCDC90B form a hetero-oligomeric complex whose stability depends on MCUR1. Deletion of MCUR1 and CCDC90B in the fission yeast Schizosaccharomyces pombe, which lacks the MCUC, impairs lipid and amino acid metabolism and causes nitrogen source-dependent growth defects that are rescued by expression of human MCUR1. Patient serum metabolomics confirms an imbalance in the amino acid pool, while MCUR1 deficiency in patient-derived skin fibroblasts upregulates autophagy, perturbs non-essential amino acid metabolism, and limits biosynthetic capacity, resulting in delayed proliferation and migration. These findings redefine the MCUR1-CCDC90B coiled-coil complex as a transmembrane scaffold critical for the integrity of mitochondrial protein complexes and the maintenance of metabolic homeostasis, suggesting a potential link between MCUR1 deficiency and human neurometabolic disease.

cell biology↗

bioRxiv2025

Targeting Kinases to Reshape the Immunopeptidome landscape in Chronic Myeloid Leukemia

Antileukemia immunity is essential for disease control and maintaining treatment-free remission in chronic myeloid leukemia (CML). Immunotherapeutic approaches hold significant promise for enhancing immune-mediated disease control. However, successful immunotherapy relies on identifying CML-associated antigens and achieving robust antigen presentation. Protein kinases are central regulators of signaling, and protein turnover, influencing which peptides are processed and presented on HLA molecules. Indeed, previous works with CDK4/6 or MEK inhibitors showed that kinases influence immune recognition of cancer cells. However, the molecular mechanisms underlying the modulation of the immunopeptidome by kinases inhibitors treatment remained unclear. Here, we investigated whether pharmacological inhibition of key kinases, including BCR-ABL, JNK and LCK, could be leveraged to reshape the immunopeptidome of CML cells, enhancing the exposure of specific tumor-associated antigens. By employing high-sensitive mass spectrometry (MS)-based immunopeptidomics, we quantified more than 20,000 HLA-I peptides. Pharmacological suppression of LCK, JNK and BCR-ABL drastically remodels the antigen landscape, impacting the exposure of about 4,000 HLA-I ligands. By integrating immunopeptidomics, phospho-immunopeptidomics, and proteomic, our study revealed three complementary molecular mechanisms of kinase-dependent antigen control: direct phosphorylation of HLA-I peptides (i), modulation of source protein stability (ii), and control of transcription factors governing antigen expression (iii). Moreover, comparative HLA ligandome analysis of benign hematological specimens and CML primary samples identified a panel of about 90 frequently presented CML-exclusive peptides, whose presentation can be significantly increased by LCK and JNK inhibition. Our study establishes a framework to rationally combine kinase inhibitors with immunotherapies to enhance antigen visibility and improve antileukemic immunity.

cancer biology↗

bioRxiv2025

Multimodal AI agents for capturing and sharing laboratory practice

We present a multimodal AI laboratory agent that captures and shares tacit experimental practice by linking written instructions with hands-on laboratory work through the analysis of video, speech, and text. While current AI tools have proven effective in literature analysis and code generation, they do not address the critical gap between documented knowledge and implicit lab practice. Our framework bridges this divide by integrating protocol generation directly from researcher-recorded videos, systematic detection of experimental errors, and evaluation of instrument readiness by comparing current performance against historical decisions. Evaluated in mass spectrometry-based proteomics, we demonstrate that the agent can capture and share practical expertise beyond conventional documentation and identify common mistakes, although domain-specific and spatial recognition should still be improved. This agentic approach enhances reproducibility and accessibility in proteomics and provides a generalizable model for other fields where complex, hands-on procedures dominate. This study lays the groundwork for community-driven, multimodal AI systems that augment rather than replace the rigor of scientific practice.

bioinformatics↗

bioRxiv2025

scPortrait integrates single-cell images into multimodal modeling

Machine learning increasingly uncovers rules of biology directly from data, enabled by large, standardized datasets. Microscopy images provide rich information on cellular architecture and are accessible at scale across biological systems, making them an ideal foundation for modeling cell behavior. However, a standardized image format does not exist at the single-cell level. Here we present scPortrait, an scverse software package for generation, storage, and application of single-cell image datasets. scPortrait reads, stitches and segments raw fields of view with out-of-core computation scaling to larger-than-memory datasets. Parallelization enables rapid extraction of individual cells into a standardized single-cell image format with fast access to accelerate machine learning. scPortrait enables analysis across modalities including images, proteomics and transcriptomics, identifying cancer-associated macrophage subpopulations by morphology and embedding single-cell images into transcriptome atlases. scPortrait turns microscopy images into a reusable resource for integrative cell modeling, establishing single-cell images as a core modality in systems biology.

systems biology↗

bioRxiv2025

Distinct and Combined Interferon-α/β-receptor-1 Loss in Neurons and Astrocytes Disrupt Brain Energy Metabolism and Drive Parkinsonian Dementia

Dysregulated interferon-alpha/beta-receptor 1 (IFNAR1) signaling was recently identified to contribute to the development of sporadic Parkinsons Disease (PD) into PD with Dementia (PDD). The molecular, cellular, and phenotypic impacts of brain IFNAR1 loss in aging have not been explored in vivo, which may reveal novel disease mechanisms and therapeutic targets. Here it is shown that baseline IFNAR1 expression varies in the major brain cell types, including neurons and astrocytes, and is differentially affected in PD and Lewy Body Dementia patients compared to unaffected controls. Neuron- and astrocyte-specific transcriptomic and proteomic alterations in Ifnar1-/- mice implicate mitochondrial defects and synergistic dysfunctional neurotransmission upon IFNAR1 loss, leading to glucose hypermetabolism measured by functional metabolic analysis. Consequently, Ifnar1-/- mice exhibited PDD-like pathogenesis, including dopaminergic cell loss in the substantia nigra, cortical neurodegeneration, Lewy-body-like inclusions, neuroinflammation, and progressive PDD-like behavior deficits. Brain cell-specific IFNAR1 loss examined in vivo revealed delayed but distinct development of PDD-like phenotypes, where neuropathology, motor, and cognitive behavior deficits were specifically recapitulated only in mice lacking neuronal IFNAR1, and behavior resembling neuropsychiatric abnormalities recapitulated only in mice lacking astrocytic IFNAR1. This work supports a crucial role of IFNAR1 in brain homeostasis and emphasizes a need for understanding neurodegenerative pathophysiology in cell-specific contexts. HighlightsO_LIIFNAR1 and related type-I IFN genes are differentially expressed among major brain cell types in Parkinsons Disease, Lewy Body Dementia, and unaffected controls C_LIO_LIEarly molecular alterations in Ifnar1-/- mice show lack of immunomodulation contributing to neuroinflammation, mitochondrial defects, and dysregulated energy metabolism C_LIO_LIIfnar1-/- mice develop a progressive Parkinsonian-like disease phenotype, including dopaminergic cell loss in substantia nigra, cortical neurodegeneration, phosphorylated (p)alpha-synuclein+ and pTau+ Lewy-body-like inclusions, neuroinflammation, and progressive motor, cognitive, and neuropsychiatric disturbance-like behavior deficits C_LIO_LINeuropathologies, motor, and cognitive deficits are recapitulated in mice lacking neuronal IFNAR1 (Syn1Cre;Ifnar1fl/fl) whereas neuropsychiatric abnormalities are recapitulated in mice lacking astrocytic IFNAR1 (GFAPCre;Ifnar1fl/fl) C_LI

neuroscience↗

bioRxiv2025

Spatial proteomics reveals mechanisms of cell-intrinsic tryptophan metabolism controlling ovarian cancer survival

Indole-2,3-dioxygenase (IDO1) depletes tryptophan to dampen anti-tumor T cells, yet IDO1 inhibitors (IDO1i) have failed clinically. Using deep visual proteomics, we isolated IDO1 high, medium and low ovarian tumor cells in situ and found IDO1 tightly linked to interferon-{gamma} (IFN-{gamma}) signaling and heterogeneously expressed. Across orthogonal models with tunable IDO1, IFN-{gamma} killed ovarian cancer via a pathway requiring IFN-{gamma} signaling, IDO1-dependent tryptophan depletion, and a biphasic integrated stress response that initially protects from starvation and later drives death. IDO1i or tryptophan supplementation rescued these effects, promoting tumor survival. These data reveal a context-dependent, tumor-suppressive facet of IDO1 and explain how IDO1i can paradoxically favor cancer viability. Our findings call for re-evaluation of IDO1 as a target and suggest exploiting the tryptophan-starvation/GCN2-ISR axis to enhance therapy.

cancer biology↗

bioRxiv2025

Replacement of a single residue in an antibody completely abolishes cognate antigen binding, as predicted by theoretical methods

Structural insights into the interaction between antibodies and antigens at the atomic level are pivotal for understanding the molecular mechanisms of antigen binding. Despite the availability of structural models generated by recent artificial intelligence advancements, computational predictions require experimental validation to confirm their accuracy. Here, we demonstrate a novel approach that combines computational protein modeling with spectroscopic experiments to validate antibody-antigen interactions. As a case example we use solanezumab, a monoclonal antibody that targets amyloid-beta (A{beta}), whose misfolding is the main factor responsible for Alzheimers disease. For this antibody we predicted a single mutation, G95AHC, within the paratope of the heavy chain to disrupt antigen binding. This mutation, referred to as a "dead mutant", was experimentally validated using an immuno-infrared biosensor (iRS). Our results confirmed that the mutation abolished antigen binding without affecting the native structure of the antibody. The use of dead mutants enables precise differentiation between specific and nonspecific binding, which is particularly important in medical diagnostics. We applied this approach to analyze the binding of solanezumab to synthetically produced A{beta} variants and A{beta} catched by the iRS functionalized surface from cerebrospinal fluid, showcasing its utility in Alzheimers disease diagnostics. These findings highlight the value of computational modeling and experimental validation in understanding antigen-antibody interactions, with significant implications for diagnostic and therapeutic applications.

biophysics↗

bioRxiv2025

A Solid-Phase Extraction Capture (SPEC) workflow in nanoliter volumes for fast, robust and ultrasensitive proteomics

Sample preparation remains a critical bottleneck in mass spectrometry (MS)-based proteomics, particularly for limited sample amounts where surface adsorption and dilution cause substantial losses. Here, we present Solid-Phase Extraction Capture (SPEC), a workflow that confines protein processing to nanoliter volumes within ion-exchange or C18 matrix inside a pipette tip. This achieves near-complete proteolysis within 5 minutes instead of hours and maintains full compatibility with strong detergents without cleanup steps, enabling effective lysis of challenging samples. From 200 ng FFPE tissue, SPEC achieves proteome depth and reproducibility exceeding conventional bulk protocols using 100 {micro}g, critical when sample is irreplaceable. The modular two-tip configuration enables on-tip chemical modifications for mTRAQ labeling and fractionation, while integration with enrichment workflows yields 2-fold improved glycopeptide identifications from plasma and 3-fold enhanced ubiquitin remnant identification at low amounts. SPEC enables nanoPhos for cell-type resolved tissue phosphoproteomics and provides a universal platform for proteomics sample preparation.

systems biology↗

bioRxiv2025

nanoPhos enables ultra-sensitive and cell-type resolved spatialphosphoproteomics

Mass spectrometry (MS)-based phosphoproteomics has transformed our understanding of cell signaling, yet current workflows face limitations in sensitivity and spatial resolution at sub-microgram inputs. Here, we present nanoPhos, a robust method that extends phosphoproteomics to nanogram scale, making it compatible with cell-type-resolved spatial analysis. It employs loss-less solid phase extraction capture (SPEC) for sample preparation, followed by automated phosphopeptide enrichment using Fe(III)-NTA cartridges. nanoPhos identifies over 57,000 unique phosphorylation sites from 1 {micro}g cell lysate and over 4,000 from only 10 ng, a hundred-fold improvement from recent protocols. Combined with Deep Visual Proteomics (DVP), it enables region- and cell-type resolved phosphoproteomics of mouse brain tissue with spatial fidelity and a depth of 13,000 phosphosites from only 1000 cell shapes. This establishes nanoPhos as a versatile and ultra-sensitive platform that extends DVP to post-translational modifications and opens up for cell-type-specific signaling analysis in intact tissue.

systems biology↗

bioRxiv2025

DCHS1 Modulates Forebrain Proportions in Modern Humans via a Glycosylation Change

Comparative anatomical studies of primates and extinct hominins, including Neanderthals, show that the modern human brain is characterised by a disproportionately enlarged neocortex relative to the striatum. To explore the molecular basis of this difference, we screened for missense mutations that are unique to modern humans and occur at high frequency and that alter post-translational sites. One such mutation was identified in DCHS1, a protocadherin family gene, and it was found to disrupt an N-glycosylation site in modern humans. Using CRISPR/Cas9-editing we introduced into human-induced pluripotent stem cells (hiPSCs) this ancestral DCHS1 variant present in Neanderthals and other primates, representing the ancestral state before the modern human-specific substitution. Leveraging hiPSCs-derived neural organoids, we observed an expansion of striatal progenitors at the expense of the neocortex, mirroring the anatomical distribution seen in non-human primates. We further identify the ephrin receptor EPHA4 as a binding partner of DCHS1 and show that modern human-specific alterations in DCHS1 modulate EPHA4-ephrin signalling, contributing to a gradual shift in the neocortex-to-striatum ratio - a hallmark of brain organisation in our species.

neuroscience↗

bioRxiv2025

Pre-Analytical Drivers of Bias in Bead-Enriched Plasma Proteomics

Bead-based enrichment has emerged as a promising strategy to improve depth in plasma proteomics by overcoming the dynamic range barrier. However, its robustness against pre-analytical variation has not been sufficiently characterized. Here, we systematically evaluate five plasma proteomics workflows--including three bead-based methods and two conventional protocols--using controlled spike-ins of low-abundance proteins and defined cellular contaminants. We find that bead-based approaches enhance detection of low-abundance proteins but can be highly susceptible to systematic bias from platelet and PBMC contamination, even at low levels. This can easily inflate results by thousands of proteins, likely accounting for some of the very high literature-reported numbers. In contrast, a perchloric acid-based workflow shows notable resistance to erythrocyte and platelet-derived contamination. We further investigate how centrifugation conditions, anticoagulant choice, and buffer-bead combinations modulate contamination profiles and demonstrate that bias can partially be mitigated by optimized sample handling. In total, we identify more than 13,000 different protein groups from various conditions, including cellular components from the circulating proteome. Our results provide a quantitative framework for assessing workflow performance under variable sample quality and offer guidance for both biomarker discovery and quality control in clinical proteomics studies.

biochemistry↗

bioRxiv2025

Design of combination therapeutics from protein response to drugs in ovarian cancer cells

High-grade serous ovarian cancer (HGSOC) remains the most lethal gynecologic malignancy, and novel treatment approaches are needed. Here, we used unbiased quantitative protein mass spectrometry to assess the cellular response profile to drug perturbations in ovarian cancer cells for the rational design of potential combination therapies. Analysis of the perturbation profiles revealed proteins responding across several drug perturbations (called frequently responsive below) as well as drug-specific protein responses. The frequently responsive proteins included proteins that reflected general drug resistance mechanisms, such as changes in drug efflux pumps. Network analysis of drug-specific protein responses revealed known and potential novel markers of resistance, which were used to rationalize the design of anti-resistance drug pairs. We experimentally tested the anti-proliferative effects of 12 of the proposed drug combinations in 6 HGSOC cell lines. While response typically varies across different cell lines, 10 of the 12 combinations tested have either an additive or synergistic CI index in at least one cell line and may therefore be plausible candidates for overcoming or preventing resistance to single agents. Serendipitously, we observed an unexpectedly strong 0.05-0.11 micromolar response to GPX4 inhibitors as single agents in the OVCAR-4 cell line. We propose several drug combinations as potential therapeutic candidates in ovarian cancer, as well as GPX4 inhibitors as single agents. HighlightsO_LI5000-protein response to 7 drugs in an ovarian cancer cell line profiled by protein mass spectrometry C_LIO_LINetwork analysis suggested potential pathways of drug resistance inferred from response profiles C_LIO_LIDemonstration of a general method for profiling adaptive response to therapeutic interventions with implications for the development of anti-resistance therapy C_LIO_LIPlausible anti-resistance drug combinations tested for antiproliferative effect in up to 6 ovarian cancer cell lines C_LIO_LIDrug combinations with additive or synergistic antiproliferative effects are plausible pre-clinical candidates for overcoming or preventing resistance to single agents C_LIO_LISeveral combinations were synergistic in some cell lines (with PARPi, MEKi, and SRCi) C_LIO_LIWe observed 0.05-0.11 micromolar response to GPX4 inhibitors as single agents in the OVCAR-4 cell line C_LI

cancer biology↗

bioRxiv2025

Multiplexed Deep Visual Proteomics Unveils Spatial Heterogeneity and Rare Endocrine States in Human Adult Pancreatic Islets

Pancreatic islets are highly specialized tissue compartments that regulate metabolism, and their dysfunction contributes to diseases such as prediabetes and diabetes. Characterizing islet morphology and cell plasticity is essential for understanding these pathophysiological states, yet high-resolution spatial proteomics remains challenging due to the islets small size and cellular complexity. Here, we present multiplexed deep visual proteomics (mxDVP), an approach that integrates high-plex imaging with ultra-sensitive mass spectrometry to achieve deep spatial proteome profiling of defined cell types in tissue sections. Enhanced segmentation, semi- automated annotation, and optimized laser microdissection enable the enrichment of rare endocrine populations that are often overlooked in single-cell analyses. mxDVP achieves deep proteome coverage of >6,000 proteins from as few as 100 cells, including low-abundance transcription factors critical for endocrine cell fate determination. By profiling over 864,000 human pancreatic cells, we identify 12 endocrine subtypes, including polyhormonal hybrids, revealing previously unrecognized islet heterogeneity, metabolic regulation, and cellular adaptability.

molecular biology↗

bioRxiv2025

In vitro model of human subcutaneous adipocyte spheroids for studying mitochondrial dysfunction and mitochondria activating compounds

Mitochondrial abnormalities drive subcutaneous white adipose tissue dysfunction in obesity, leading to metabolic complications. A key challenge in obesity research is the lack of in vitro models to study human adipocyte mitochondria. Here, we establish a human subcutaneous adipocyte spheroid model to characterize mitochondrial metabolism under obesity-relevant conditions and drug exposure. Human preadipocyte spheroids were differentiated in ultra-low attachment plates for 3 weeks in media free of thiazolidinediones. The differentiated adipocyte spheroids showed increased lipid accumulation, adipogenic gene expression, mitochondrial respiration and adiponectin secretion, and a proper response to hormonal stimulation. Lipid mixture administration during differentiation induced metabolic disturbances including mitochondrial respiration failure associated with increased mitochondrial biogenesis. Post-differentiation treatment with rosiglitazone, a peroxisome proliferator-activated receptor {gamma} agonist, improved mitochondrial bioenergetics and adiponectin secretion in lipid mixture-administered adipocyte spheroids. Our model enables precise measurement of adipocyte mitochondria under various conditions, providing a platform for mitochondria-related research and drug discovery in obesity.

molecular biology↗

bioRxiv2025

Single cell spatial proteomics maps human liver zonation patterns and their vulnerability to fibrosis

Understanding protein distribution patterns across tissue architecture is crucial for deciphering organ function in health and disease. Here, we applied single-cell Deep Visual Proteomics to perform spatially-resolved proteome analysis of individual cells in native tissue. We combined this with a novel strategic cell selection pipeline and a continuous protein gradient mapping framework to investigate larger clinical cohorts. We generated a comprehensive spatial map of the human hepatic proteome by analyzing hundreds of individual hepatocytes from 18 individuals. Among more than 2,500 proteins per cell about half exhibited zonated expression patterns. Cross-species comparison with mouse data revealed conserved metabolic functions and human-specific features of liver zonation. Analysis of fibrotic samples demonstrated widespread disruption of protein zonation, with pericentral proteins being particularly susceptible. Our study provides a comprehensive resource of human liver organization while establishing a broadly applicable framework for spatial proteomics analyses along tissue gradients.

molecular biology↗