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Temporal and spatial omics technologies for 4D profiling.

David E Reynolds1, Yoon Ho Roh2,3, Daniel Oh1

  • 1Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.

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|April 22, 2025
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Summary

Capturing cell dynamics requires advanced spatial omics. This perspective explores temporal and 3D spatial omics fusion and 4D profiling for deeper biological insights.

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Area of Science:

  • Molecular biology
  • Cell biology
  • Biotechnology

Background:

  • Cells possess unique surface and intracellular molecular profiles crucial for biological responses.
  • Understanding cellular dynamics in growth, development, and disease is limited by challenges in capturing temporal and spatial characteristics.
  • Existing omics techniques struggle to provide a comprehensive view of living cells over time and space.

Purpose of the Study:

  • To review techniques for temporal and 2D/3D spatial omics analyses.
  • To highlight the potential of fusing these techniques for understanding cellular dynamics.
  • To explore the emerging field of four-dimensional (4D) profiling in biological systems.

Main Methods:

  • Discussion of temporal omics techniques.
  • Analysis of 2D and 3D spatial omics methodologies.
  • Exploration of the integration of temporal and spatial omics data.
  • Review of advancements and challenges in 4D profiling.

Main Results:

  • The fusion of temporal and spatial omics offers powerful insights into cell dynamics and diversity.
  • Four-dimensional profiling, integrating time with 3D spatial omics, represents a promising frontier.
  • Current technologies face challenges in precise temporal and spatial resolution.
  • Further technological development is needed to fully realize the potential of 4D profiling.

Conclusions:

  • Integrating temporal and spatial omics is key to unlocking a deeper understanding of cellular behavior.
  • Four-dimensional profiling holds significant promise for future biological research.
  • Addressing current technological gaps will accelerate advancements in single-cell analysis.