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Adaptive prediction of environmental changes by microorganisms

Author

Listed:
  • Amir Mitchell

    (Weizmann Institute of Science Rehovot 76100)

  • Gal H. Romano

    (Tel Aviv University, Tel Aviv 69978, Israel)

  • Bella Groisman

    (Weizmann Institute of Science Rehovot 76100)

  • Avihu Yona

    (Weizmann Institute of Science Rehovot 76100)

  • Erez Dekel

    (Weizmann Institute of Science Rehovot 76100)

  • Martin Kupiec

    (Tel Aviv University, Tel Aviv 69978, Israel)

  • Orna Dahan

    (Weizmann Institute of Science Rehovot 76100)

  • Yitzhak Pilpel

    (Weizmann Institute of Science Rehovot 76100
    Harvard Medical School, Boston, Massachusetts 02115, USA)

Abstract

Natural habitats of some microorganisms may fluctuate erratically, whereas others, which are more predictable, offer the opportunity to prepare in advance for the next environmental change. In analogy to classical Pavlovian conditioning, microorganisms may have evolved to anticipate environmental stimuli by adapting to their temporal order of appearance. Here we present evidence for environmental change anticipation in two model microorganisms, Escherichia coli and Saccharomyces cerevisiae. We show that anticipation is an adaptive trait, because pre-exposure to the stimulus that typically appears early in the ecology improves the organism’s fitness when encountered with a second stimulus. Additionally, we observe loss of the conditioned response in E. coli strains that were repeatedly exposed in a laboratory evolution experiment only to the first stimulus. Focusing on the molecular level reveals that the natural temporal order of stimuli is embedded in the wiring of the regulatory network—early stimuli pre-induce genes that would be needed for later ones, yet later stimuli only induce genes needed to cope with them. Our work indicates that environmental anticipation is an adaptive trait that was repeatedly selected for during evolution and thus may be ubiquitous in biology.

Suggested Citation

  • Amir Mitchell & Gal H. Romano & Bella Groisman & Avihu Yona & Erez Dekel & Martin Kupiec & Orna Dahan & Yitzhak Pilpel, 2009. "Adaptive prediction of environmental changes by microorganisms," Nature, Nature, vol. 460(7252), pages 220-224, July.
    • Handle: RePEc:nat:nature:v:460:y:2009:i:7252:d:10.1038_nature08112
    DOI: 10.1038/nature08112
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    Cited by:

    1. Peter A. Corning, 2014. "Systems Theory and the Role of Synergy in the Evolution of Living Systems," Systems Research and Behavioral Science, Wiley Blackwell, vol. 31(2), pages 181-196, March.
    2. David A Sivak & Matt Thomson, 2014. "Environmental Statistics and Optimal Regulation," PLOS Computational Biology, Public Library of Science, vol. 10(9), pages 1-12, September.
    3. Alexander Tschantz & Anil K Seth & Christopher L Buckley, 2020. "Learning action-oriented models through active inference," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-30, April.
    4. Sébastien Boyer & Lucas Hérissant & Gavin Sherlock, 2021. "Adaptation is influenced by the complexity of environmental change during evolution in a dynamic environment," PLOS Genetics, Public Library of Science, vol. 17(1), pages 1-27, January.
    5. Xuesong Yang & Linfeng Lan & Ibrahim Tahir & Zainab Alhaddad & Qi Di & Liang Li & Baolei Tang & Panče Naumov & Hongyu Zhang, 2024. "Logarithmic and Archimedean organic crystalline spirals," Nature Communications, Nature, vol. 15(1), pages 1-11, December.

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