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Single-cell Microinjection for Cell Communication Analysis
Published on: February 26, 2017
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The Evolution of Cell Communication: The Road not Taken
1Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, California, U.S.
Summary
Evolutionary biology is reframed as cell communication, from unicellular to multicellular organisms and reproduction. This model predicts the evolution of physiological systems and aids in identifying genes for evolutionary changes.
Area of Science:
- Evolutionary Biology
- Developmental Biology
- Genomics
- Cell Communication
Background:
- The post-genomic era necessitates new approaches to understanding evolutionary biology.
- Existing top-down and bottom-up methods are insufficient for capturing the emergent nature of evolution.
- A middle-out approach, linking developmental biology and functional genomics, is proposed.
Purpose of the Study:
- To develop a working model for lung evolution using a middle-out, reverse-engineering strategy.
- To reduce evolutionary biology to fundamental principles of cell communication.
- To formulate testable hypotheses for the origins of physiological systems and identify candidate genes.
Main Methods:
- Reverse-engineering lung surfactant from mammalian lungs to fish swim bladders.
- Modeling evolutionary biology as a progression of cell communication: environment, cell-cell, and intergenerational.
- Utilizing functional genomic significance to identify signaling mechanisms.
Main Results:
- A cell-molecular model for lung evolution was configured, tracing it back to fish swim bladders.
- Evolutionary biology was successfully reduced to cell communication across different organismal complexities.
- The model predicts the evolution of physiological systems (development, homeostasis, aging) as a consequence of entropy reduction.
Conclusions:
- This approach offers a novel framework for evolutionary biology, focusing on cell communication and entropy reduction.
- It enables the formulation of refutable hypotheses and identifies candidate genes for evolutionary changes.
- The model lays the groundwork for predictive medicine and molecular bioethics, moving beyond correlational 'Just So Stories'.
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