Dataset Information

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.

ABSTRACT:

Background

Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it is important to measure cellular or genetic features as a function of position along a zonal axis. While it is possible to manually count, characterize, and locate features in relation to the zonal axis, it is labor-intensive and difficult to do manually while maintaining precision and accuracy.

Methods

We addressed this challenge by developing a deep-learning-based quantification method called the "Tissue Positioning System" (TPS), which can automatically analyze zonation in the liver lobule as a model system.

Findings

By using algorithms that identified vessels, classified vessels, and segmented zones based on the relative position along the portal vein to central vein axis, TPS was able to spatially quantify gene expression in mice with zone specific reporters.

Interpretation

TPS could discern expression differences between zonal reporter strains, ages, and disease states. TPS could also reveal the zonal distribution of cells previously thought to be positioned randomly. The design principles of TPS could be generalized to other tissues to explore the biology of zonation.

Funding

CPRIT (RP190208, RP220614, RP230330) and NIH (P30CA142543, R01AA028791, R01CA251928, R01DK1253961, R01GM140012, 1R01GM141519, 1R01DE030656, 1U01CA249245). The Pollack Foundation, Simmons Comprehensive Cancer Center Cancer & Obesity Translational Pilot Award, and the Emerging Leader Award from the Mark Foundation For Cancer Research (#21-003-ELA).

SUBMITTER: Rong R

PROVIDER: S-EPMC10365985 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.

Rong Ruichen R Wei Yonglong Y Li Lin L Wang Tao T Zhu Hao H Xiao Guanghua G Wang Yunguan Y

EBioMedicine 20230713

<h4>Background</h4>Tissues such as the liver lobule, kidney nephron, and intestinal gland exhibit intricate patterns of zonated gene expression corresponding to distinct cell types and functions. To quantitatively understand zonation, it is important to measure cellular or genetic features as a function of position along a zonal axis. While it is possible to manually count, characterize, and locate features in relation to the zonal axis, it is labor-intensive and difficult to do manually while m ...[more]

PMID: 37453365

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Dataset Information

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.

Background

Methods

Findings

Interpretation

Funding

Publications

Image-based quantification of histological features as a function of spatial location using the Tissue Positioning System.

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