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Adaptive prediction of environmental changes by microorganisms
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.
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“Subsequently, it was discovered that this glucose tolerant phenotype was due to an in-frame deletion in the glucose regulator MTH1, which led to altered stability of the MTH1 encoded protein [151].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [151]
Citations
Cites
Genomic Expression Programs in the Response of Yeast Cells to Environmental Changes
Gasch, A. P., Spellman, P. T., Kao, C. M., Carmel-Harel, O., Eisen, M. B., Storz, G., Botstein, D., & Brown, P. O. (2000) · Molecular Biology of the Cell · doi:10.1091/mbc.11.12.4241 · Cited by 4,815
The Gene Ontology (GO) database and informatics resource
Gene Ontology Consortium (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh036 · Cited by 4,596
Functional Characterization of the S. cerevisiae Genome by Gene Deletion and Parallel Analysis
Winzeler, E. A., Shoemaker, D. D., Astromoff, A., Liang, H., Anderson, K., Andre, B., Bangham, R., Benito, R., Boeke, J. D., Bussey, H., et al. (1999) · Science · doi:10.1126/science.285.5429.901 · Cited by 3,953
Bacterial Persistence as a Phenotypic Switch
Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L., & Leibler, S. (2004) · Science · doi:10.1126/science.1099390 · Cited by 2,952
Remodeling of Yeast Genome Expression in Response to Environmental Changes
Causton, H. C., Ren, B., Koh, S. S., Harbison, C. T., Kanin, E. I., Jennings, E. G., Lee, T. I., True, H. L., Lander, E. S., & Young, R. A. (2001) · Molecular Biology of the Cell · doi:10.1091/mbc.12.2.323 · Cited by 1,382
Phenotypic Diversity, Population Growth, and Information in Fluctuating Environments
Kussell, E. L., & Leibler, S. (2005) · Science · doi:10.1126/science.1114383 · Cited by 1,357
Stochastic switching as a survival strategy in fluctuating environments
Açar, M., Mettetal, J. T., & van Oudenaarden, A. (2008) · Nature Genetics · doi:10.1038/ng.110 · Cited by 899
Optimality and evolutionary tuning of the expression level of a protein
Dekel, E., & Alon, U. (2005) · Nature · doi:10.1038/nature03842 · Cited by 766
Self-citationA comprehensive library of fluorescent transcriptional reporters for Escherichia coli
Zaslaver, A., Bren, A., Ronen, M., Itzkovitz, S., Kikoin, I., Shavit, S., Liebermeister, W., Surette, M. G., & Alon, U. S. (2006) · Nature Methods · doi:10.1038/nmeth895 · Cited by 748
WormBase: a multi-species resource for nematode biology and genomics
Harris, T. W. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh066 · Cited by 717
Flagged first, then by citations
Research works printed but not linked: 2
- Pavlov, I. P. Conditioned Reflexes (Oxford Univ. Press, 1927)
- Johnston, M. & Carlson, M. in The Molecular Biology of the Yeast Saccharomyces: Gene Expression (eds Jones, E. W., Pringle, J. R. & Broach, J. R.) 193–282 (Cold Spring Harbor Laboratory, 1992)
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Leggett, H. C., Brown, S. P., & Reece, S. E. (2014) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2013.0365 · Cited by 77
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Caspeta, L., Chen, Y., & Nielsen, J. (2016) · Scientific Reports · doi:10.1038/srep27003 · Cited by 66
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Boyer, S., Hérissant, L., & Sherlock, G. J. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009314 · Cited by 48
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Lyon, P. (2017) · Biology & Philosophy · doi:10.1007/s10539-017-9567-1 · Cited by 40
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Partner or perish: tree microbiomes and climate change.
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Connor, K. M., & Gracey, A. Y. (2020) · Marine Biology · doi:10.1007/s00227-020-03750-6 · Cited by 35
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Metadata
- Authors
- Mitchell, A., Romano, G. H., Groisman, B., Yona, A., Dekel, E., Kupiec, M., Dahan, O., & Pilpel, Y.
- Affiliations
- Weizmann Institute of Science (IL)
- Tel Aviv University (IL)
- Harvard University (US)
- Corresponding author
- Pilpel, Yitzhak
- Venue
- Nature
- Published
- 2009-06-17
- Volume
- 460
- Issue
- 7252
- Pages
- 220-224
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2165081628
- Cited by
- 581
- References
- 28
- Citations by year
- 2026: 26 · 2025: 28 · 2024: 31 · 2023: 47 · 2022: 38 · 2021: 32 · 2020: 40 · 2019: 35 · 2018: 57 · 2017: 37 · 2016: 30 · 2015: 30 · 2014: 27 · 2013: 30 · 2012: 30
- FWCI
- 12.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- European Science Foundation
- Israel Science Foundation
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
- Keywords
- classical conditioning, Escherichia coli, Saccharomyces cerevisiae, gene expression regulation, regulatory networks, adaptive evolution, conditioned response, memory loss, fitness, gut microbiota, yeast fermentation
- MeSH terms
- Adaptation, Physiological, Carbon, Environment, Escherichia coli, Biological Evolution, Fermentation, Gene Expression Regulation, Lactose, Maltose, Osmotic Pressure, Saccharomyces cerevisiae, Time Factors, Oxidative Stress, Heat-Shock Response, Cell Respiration, Genomics, Carbohydrate Metabolism
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