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Related Experiment Video

Updated: May 7, 2026

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

Published on: April 30, 2019

Neighborhood-informed positional information for precise cell identity specification.

Michal Erez¹, Roy Friedman¹, Mor Nitzan^2,3,4

¹School of Computer Science and Engineering, The Hebrew University, Jerusalem, Israel.

Molecular Systems Biology

|May 5, 2026

Summary

This summary is machine-generated.

Cells use gene expression patterns to determine their position during development. Neighboring cells provide crucial information, closing the positional information gap and ensuring accurate cell identity specification.

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Area of Science:

Developmental biology
Systems biology
Computational biology

Background:

Cellular identity is established during development through positional information encoded in gene expression.
Cells in Drosophila embryos can determine their position along the anterior-posterior axis with 1% precision, but this is insufficient for unique identification.

Purpose of the Study:

To propose an information-theoretic framework to quantify positional information from cellular microenvironments.
To investigate how neighborhood information complements individual cell data for precise positional decoding.

Main Methods:

Developed a neighborhood-informed information-theoretic framework.
Quantified additional positional information from neighboring cells based on spatial gene expression variation.
Utilized neighborhood-informed decoders for position and gene expression prediction.

Main Results:

Neighborhood information is sufficient to uniquely specify cell identities, closing the positional information gap.
This holds true across major patterning axes in Drosophila embryos, gastruloids, and developing neural tubes.
Neighborhood-informed decoders achieve higher accuracy and lower variability in predicting cell positions and gene expression compared to cell-independent decoders.

Conclusions:

Cellular microenvironments play a critical role in refining positional information during development.
The proposed framework provides a quantitative basis for understanding cell decision-making within their local context.
This approach enhances the accuracy of predicting cell fate and position in various developmental systems.