bioRxivBioinformaticsPreprint
Systematic Analysis of Human Tissue- and Cell-Specific Metabolic Models Identifies High-Sugar, High Fat Diet Induced Liver Dysregulation
Mengzhen Li, Mengnan ShiiD, Cheng ZhangiD, Hasan TürkeziD, Mathias UhléniD, Adil MardinoğluiD
Abstract
Human tissues exhibit specialized metabolic functions that are essential for maintaining whole-body metabolic homeostasis. To systematically characterize organ- and cell-type-specific metabolic heterogeneity, we constructed 32 tissue-specific and 81 cell-type-specific enzyme-constrained genome-scale metabolic models (ecGEMs) by integrating the global human metabolic network with the tissue- and single-cell transcriptomic data from the Human Protein Atlas (HPA). Our analysis revealed pronounced differences in metabolic network architecture and activity across the human body, identifying key cell types that drive tissue metabolic functions. To demonstrate the applicability of these models, we employed the liver-specific ecGEM to investigate the metabolic reprogramming induced by a high-sugar, high-fat (HSHF) diet, a primary driver of metabolic dysfunction-associated fatty liver disease (MAFLD). Flux balance analysis revealed a fundamental transition in hepatic metabolism: from a flexible, multi-functional system toward a constrained, lipid-centric regime. This state is characterized by carbohydrate and lipid overload, mitochondrial respiratory dysfunction, and a compromised capacity for reactive oxygen species (ROS) detoxification. These computational predictions were validated through integrative analysis of transcriptomic data from a human MAFLD cohort and metabolomic profiles from an in vivo HSHF rat model. Together, this work provides a comprehensive atlas of human metabolic models, enabling the systematic investigation of metabolic features across tissues and conditions from a systems-level perspective. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/706568v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@1015c7org.highwire.dtl.DTLVardef@5c200org.highwire.dtl.DTLVardef@3c982org.highwire.dtl.DTLVardef@a2894d_HPS_FORMAT_FIGEXP M_FIG C_FIG
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Modeling tissue-specific Drosophila metabolism identifies high sugar diet-induced metabolic dysregulation in muscle at reaction and pathway levels
Sun Jin Moon, Yanhui Hu, … Norbert Perrimon·bioRxiv·Apr 24, 2024
- Energy metabolism adaptations and gene expression reprogramming in a cellular MAFLD model
T.-R. Zhou, C. Cömert, … P. Bross·bioRxiv·Nov 8, 2021
- Physiologically relevant media are associated with overlapping metabolic responses in primary human hepatocytes and Huh7 cells
Eloise Cross, Felix Westcott, … Leanne Hodson·Physiological ReportsPeer-reviewed·Jul 1, 2026
- Epigenetic control of metabolic identity across cell types
Maria Pires Pacheco, Déborah Gérard, … Thomas Sauter·BMC GenomicsPeer-reviewed·Dec 10, 2025
- Differences in metabolic and liver pathobiology induced by two dietary mouse models of nonalcoholic fatty liver disease
H. Zhang, M. Leveille, … J. L. Estall·bioRxiv·Jun 5, 2020
- An atlas of the human metabolome
Jeremy K. Chan, Nicholas S Ly, … J. Rafael Montenegro-Burke·bioRxiv·May 22, 2026