Reintegrating Biology Through the Nexus of Energy, Information, and Matter

Author:

Hoke Kim L1,Zimmer Sara L2,Roddy Adam B3,Ondrechen Mary Jo4,Williamson Craig E5,Buan Nicole R6

Affiliation:

1. Department of Biology, Colorado State University, Fort Collins, CO 80523-1878, USA

2. Department of Biomedical Sciences, University of Minnesota Medical School, Duluth campus, Duluth, MN 55812, USA

3. Department of Biological Sciences, Institute of Environment, Florida International University, Miami, FL 33199, USA

4. Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA 02115, USA

5. Department of Biology, Miami University, Oxford, OH 45056, USA

6. Department of Biochemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0662, USA

Abstract

Synopsis Information, energy, and matter are fundamental properties of all levels of biological organization, and life emerges from the continuous flux of matter, energy, and information. This perspective piece defines and explains each of the three pillars of this nexus. We propose that a quantitative characterization of the complex interconversions between matter, energy, and information that comprise this nexus will help us derive biological insights that connect phenomena across different levels of biological organization. We articulate examples from multiple biological scales that highlight how this nexus approach leads to a more complete understanding of the biological system. Metrics of energy, information, and matter can provide a common currency that helps link phenomena across levels of biological organization. The propagation of energy and information through levels of biological organization can result in emergent properties and system-wide changes that impact other hierarchical levels. Deeper consideration of measured imbalances in energy, information, and matter can help researchers identify key factors that influence system function at one scale, highlighting avenues to link phenomena across levels of biological organization and develop predictive models of biological systems.

Funder

NSF

NRB

USDA

NIH

Publisher

Oxford University Press (OUP)

Subject

Plant Science,Animal Science and Zoology

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