1. European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69012 Heidelberg, Germany
2. Department of Zoology, University of Oxford, Oxford OX1 3PS, UK
3. Faculty of Life Sciences, The University of Manchester, Michael Smith Building, Oxford Road, Manchester M13 9PT, UK
4. Department of Biology & Biochemistry, University of Bath, Claverton Down, Bath BA2 7AY, UK
5. Department of Medical Chemistry, Semmelweis University, PO Box 260, H-1444 Budapest, Hungary
6. *These authors contributed equally to this work

Correspondence to: Laurence D. Hurst⁴ Correspondence and requests for materials should be addressed to L.D.H. (Email: l.d.hurst@bath.ac.uk).

Abstract

It is possible to infer aspects of an organism's lifestyle from its gene content¹. 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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