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Background <p>Recent advancements in single-cell transcriptomic analyses have greatly expanded our understanding of cellular diversity in adipose tissue, indicating transcriptionally distinct subpopulations of adipocytes. Here we sought to rigorously test such heterogeneity at the protein level.</p> Methods <p>A data-driven imaging platform was tailored to assess cellular protein levels based on immunofluorescence staining in primary adipocytes isolated from human adipose tissue biopsies (abdominal and gluteal adipose tissue from <i>n</i> = four subjects). Isolated adipocytes were co-labeled for GLUT4 and the previously proposed adipocyte subtype markers PLIN1 and DDR2 to assess their relative expression levels.</p> Results <p>The platform enabled a two-step gating, shape-based filtering approach, which allowed accurate identification of mature adipocytes of a large cell-size range. The software was able to accurately detect hundreds of adipocytes spanning a broad size range. When comparing cells isolated from a single adipose tissue depot and subject, we found that a large proportion of cells had relatively high levels of both DDR2 and PLIN1. No notable differences in GLUT4 levels were observed within this group of cells.</p> Conclusions <p>The described approach, based on population-wide imaging, could serve as a robust tool to further validate cellular characteristics at a single-cell level. The fact that we detected distinct protein levels of the proposed adipocyte markers may reflect the presence of mature adipocyte subtypes.</p>

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Characterization of white adipocyte heterogeneity using data-driven microscopy

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月8日

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  • Jieyu Zhang,
  • Christian Simonsson,
  • Ayesha Fawad,
  • Wathik Alsalim,
  • Allan Vaag,
  • Mathis Neuhaus,
  • Karin G. Stenkula

摘要

Background

Recent advancements in single-cell transcriptomic analyses have greatly expanded our understanding of cellular diversity in adipose tissue, indicating transcriptionally distinct subpopulations of adipocytes. Here we sought to rigorously test such heterogeneity at the protein level.

Methods

A data-driven imaging platform was tailored to assess cellular protein levels based on immunofluorescence staining in primary adipocytes isolated from human adipose tissue biopsies (abdominal and gluteal adipose tissue from n = four subjects). Isolated adipocytes were co-labeled for GLUT4 and the previously proposed adipocyte subtype markers PLIN1 and DDR2 to assess their relative expression levels.

Results

The platform enabled a two-step gating, shape-based filtering approach, which allowed accurate identification of mature adipocytes of a large cell-size range. The software was able to accurately detect hundreds of adipocytes spanning a broad size range. When comparing cells isolated from a single adipose tissue depot and subject, we found that a large proportion of cells had relatively high levels of both DDR2 and PLIN1. No notable differences in GLUT4 levels were observed within this group of cells.

Conclusions

The described approach, based on population-wide imaging, could serve as a robust tool to further validate cellular characteristics at a single-cell level. The fact that we detected distinct protein levels of the proposed adipocyte markers may reflect the presence of mature adipocyte subtypes.