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Human Liver Cells: Zooming in on Functional Heterogeneity

Featured Publication, Pioneer Campus,

Scientists from the PioneerCampus at Helmholtz Munich unraveled rather transcriptionally distinct subgroups of human hepatocytes with relevance to human disease and personalized treatment.

Human liver hepatocytes are central to our bodies’ vast metabolic functions, the detoxification of xenobiotics and drugs as well as for protein synthesis. Therefore, efficacy and safety of newly developed compounds are routinely tested in primary human hepatocytes as gold standard. However, recent single-cell data surfaced a somewhat surprising ‚division of labor‘ in hepatocytes – a level of cellular heterogeneity potentially encoded in structural cues (such as liver zonation) or correlating with cellular features, like ploidy.

Scientists from the HPC at Helmholtz Munich recently published a study in Genome Biology aimed at uncovering - and the first molecular characterization – of potential functional heterogeneity in human liver hepatocytes. For this, primary human hepatocytes were exposed to metabolic stress or multi-drug treatments – mimicking chronic liver disease such as fatty liver disease, or patients in need of multi-drug medication.

Single cell transcriptomic analyses of commercially available, human primary hepatocytes allowed the researchers to annotate four distinct hepatocyte subgroups – with three of them presenting metabolic active states, but statistically robust differential transcriptional profiles indicating unique and diverse metabolic specialization. Intriguingly, all three could be computationally mapped onto published in-vivo data sets from human livers, establishing a correlation between in vivo and in vitro annotations and subgroup specializations.

Crucially, the exposure to an industry-standard five-drug cocktail corroborated rather distinct metabolic profiles and capacity in the newly discovered hepatocyte subgroups – a conclusion derived from subgroup-specific gene expression profiles in line with the concept of hepatocyte (population) heterogeneity. Further corroboration comes indeed from treatments that mimic hepatic steatosis, a frequent condition in obese patients suffering from fat accumulation in the liver or during aging. While the transcriptional variability was increased in subgroups I and II, subgroup III responded with a general though coordinated gene transcription and reduced transcriptional variability.Ultimately, and to this end not too surprising, subgroup-specific drug/xenobiotic-metabolic gene expression profiles were impaired under steatosis-mimicking conditions.

Previous results proposed – in a general sense – heterogeneity within seemingly homogeneous hepatocyte populations. Such a notion may have a tremendous impact on liver (cell) function – and hence crucial clinical decisions as far as the actual metabolic capacity, regenerative potential and treatment regimes, and respective decisions on liver transplantation are concerned. However, detailed and single-cell resolved functional analyses substantiating the notion of hepatocyte heterogeneity – and hence informing future clinical decision making are sparse.

The presented, robust, genome-scale datasets are therefore a first intriguing treasure-throve for scientists and clinicians to thoroughly drill into the molecular features of functionally distinct hepatocyte populations. They should thus enable the derivation of novel potential biomarker and diagnostic tools to distinctly stratify liver damage in clinical settings, paving the way for genuine, evidence-based personalized medicine.

Atdaped article from the Helmholtz Pioneer Campus 

original publication

Eva Sanchez-Quant, Maria Lucia Richter, Maria Colomé-Tatché & Celia Pilar Martinez-Jimenez (2023): Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge. Genome Biology. DOI:

About the scientist 

Dr. Celia P. Martinez-Jimenez, Principal Investigator for Molecular Ageing at Helmholtz Pioneer Campus at Helmholtz Munich