Isolation of primary hepatocytes and non-parenchymal cells from mouse fatty liver

In the early stages of metabolism-associated fatty liver disease (MAFLD), lipid accumulation occurs in the parenchymal cells (hepatocytes, HPCs) of the liver, manifested by an increase in the number of lipid droplets within hepatocytes and an overall decrease in cellular density. Intercellular communication among different liver cell types influences hepatic lipid accumulation, making the impact of non-parenchymal cells (NPCs)on HPCs particularly significant. In vitro HPC models have been well-established and widely applied in MAFLD research. However, the altered microenvironment in MAFLD and cross-contamination between HPCs and NPCs make gene expression research in a single cell type imprecise. To more precisely detect differential gene expression between the two cell types, we enhanced cleaning details during HPC extraction using the perfusion method and adjusted the Percoll concentration gradient to 25%/60% during NPCs extraction. Compared with the previous method, our results show higher cell viability of 94.3% for HPCs and 91.4% for NPCs in the livers of HFD (High Fat Diet) mice. Furthermore, the purity of HPCs and NPCs is higher. This methodological refinement enables accurate quantification of intercellular differences in gene expression, opening new avenues to delineate the role of cell-cell crosstalk in MAFLD pathogenesis.

Authors

Institutions

Publication Details

Journal
MethodsX
Published
2026-03-01
DOI
https://doi.org/10.1016/j.mex.2026.103888
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Isolation of primary hepatocytes and non-parenchymal cells from mouse fatty liver

Yunan Shi, Huabing Zhang, Kai You Wang, Jiali Li et al.
MethodsX
Single-cell and spatial transcriptomics
article

Isolation of primary hepatocytes and non-parenchymal cells from mouse fatty liver

Yunan Shi, Huabing Zhang, Kai You Wang, Jiali Li, Xiuyun Wang, Xinzhe Zhuo, Jiao Yu, Ailipire Tudimaimaiti, Xiang Wang
article en

Abstract

In the early stages of metabolism-associated fatty liver disease (MAFLD), lipid accumulation occurs in the parenchymal cells (hepatocytes, HPCs) of the liver, manifested by an increase in the number of lipid droplets within hepatocytes and an overall decrease in cellular density. Intercellular communication among different liver cell types influences hepatic lipid accumulation, making the impact of non-parenchymal cells (NPCs)on HPCs particularly significant. In vitro HPC models have been well-established and widely applied in MAFLD research. However, the altered microenvironment in MAFLD and cross-contamination between HPCs and NPCs make gene expression research in a single cell type imprecise. To more precisely detect differential gene expression between the two cell types, we enhanced cleaning details during HPC extraction using the perfusion method and adjusted the Percoll concentration gradient to 25%/60% during NPCs extraction. Compared with the previous method, our results show higher cell viability of 94.3% for HPCs and 91.4% for NPCs in the livers of HFD (High Fat Diet) mice. Furthermore, the purity of HPCs and NPCs is higher. This methodological refinement enables accurate quantification of intercellular differences in gene expression, opening new avenues to delineate the role of cell-cell crosstalk in MAFLD pathogenesis.

MethodsX
Anhui Medical University (CN), Anhui Academy of Medical Sciences (CN), First Affiliated Hospital of Anhui Medical University (CN)
Openalex Percentile: Top 6%
Single-cell and spatial transcriptomics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.