Neighborhood-informed positional information for precise cell identity specification

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.