Chance and necessity in the evolution of minimal metabolic networks
Abstract
It is possible to infer aspects of an organism's lifestyle from its gene content. Can the reverse also be done? Here we consider this issue by modelling evolution of the reduced genomes of endosymbiotic bacteria. The diversity of gene content in these bacteria may reflect both variation in selective forces and contingency-dependent loss of alternative pathways. Using an in silico representation of the metabolic network of Escherichia coli, we examine the role of contingency by repeatedly simulating the successive loss of genes while controlling for the environment. The minimal networks that result are variable in both gene content and number. Partially different metabolisms can thus evolve owing to contingency alone. The simulation outcomes do preserve a core metabolism, however, which is over-represented in strict intracellular bacteria. Moreover, differences between minimal networks based on lifestyle are predictable: by simulating their respective environmental conditions, we can model evolution of the gene content in Buchnera aphidicola and Wigglesworthia glossinidia with over 80% accuracy. We conclude that, at least for the particular cases considered here, gene content of an organism can be predicted with knowledge of its distant ancestors and its current lifestyle.
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For eukaryotic host organisms such as yeasts, alternating asexual and sexual propagation during selection can be applied in order to decouple beneficial and unsound mutations and thus reduce potential deficits of laboratory evolution experiments.
“Moreover, for eukaryotic host organisms such as yeasts, alternating asexual and sexual propagation during selection can be applied in order to decouple beneficial and unsound mutations and thus reduce potential deficits of laboratory evolution experiments [118].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [118]
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- Authors
- Pál, C., Papp, B., Lercher, M. J., Csermely, P., Oliver, S. G., & Hurst, L. D.
- Affiliations
- European Molecular Biology Laboratory (DE)
- University of Manchester (GB)
- Semmelweis University (HU)
- University of Bath (GB)
- Corresponding author
- Hurst, Laurence D.
- Venue
- Nature
- Published
- 2006-03
- Volume
- 440
- Issue
- 7084
- Pages
- 667-670
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2139553051
- Cited by
- 239
- References
- 31
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 7 · 2023: 4 · 2022: 14 · 2021: 2 · 2020: 6 · 2019: 4 · 2018: 12 · 2017: 12 · 2016: 10 · 2015: 10 · 2014: 10 · 2013: 15 · 2012: 18
- FWCI
- 9.78
- 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)
- Research Explorer (The University of Manchester) (submittedVersion)
- Funders
- Biotechnology and Biological Sciences Research Council (E19354)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Microbial Metabolic Engineering and Bioproduction
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Life Sciences › Agricultural and Biological Sciences › Insect Science › Insect symbiosis and bacterial influences
- Keywords
- gene loss, contingency, endosymbiotic bacteria, Buchnera aphidicola, Wigglesworthia glossinidia, Escherichia coli, genome reduction, metabolic network simulation, core metabolism, symbionts, non-essential genes
- MeSH terms
- Biological Evolution, Genes, Bacterial, Symbiosis, Genome, Bacterial, Computational Biology, Buchnera, Gene Transfer, Horizontal, Escherichia coli Proteins, Wigglesworthia, Escherichia coli K12
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