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1 The maintenance of sex in bacteria is ensured by its potential to reload genes Gergely J. Szöllősi1 , Imre Derényi1 and Tibor Vellai2 Keywords: Genome evolution, Evolution of recombination, Genome organization dynamics Sexual reproduction is a process that brings genomes, or portions of genomes, from different individuals into a common cell, producing a new combination of genes: in eukaryotes, this occurs as a result of fertilization and meiotic recombination; in bacteria, it happens as a result of natural genetic transformation (NGT), a process by which bacteria actively take up exogenous DNA and use it to replace homologous chromosomal sequences. The persistence of NGT raises the same question as the prevalence of meiotic sex [OL02]: What is the short-term advantage of genetic mixing to the individual? Despite the ubiquity of genetic transfer in bacteria, which is reflected in the dynamic structure of their genomes that is constantly being shaped by two opposing forces: selection for shorter length (favoring DNA loss through deletion) and selection for gene function (driving genome loading by the acquisition of exogenous DNA)[MOM01], it has been demonstrated[R97], that the role of NGT in repairing deleterious mutations under constant selection is insufficient for its survival. The lack of other viable explanations have left no alternative except that DNA uptake provides nucleotides for food. We have developed a novel simulation approach for the long-term dynamics of genome organization (involving the loss and acquisition of genes) in a bacterial species consisting of a large number of spatially distinct populations subject to independently fluctuating ecological conditions. We view a bacterial species as a metapopulation[H98] that is composed of a large number of spatially distinct populations that experience selection for different combinations of numerous possible environmental factors (availability of particular metabolites, host recognition and others). Most of these factors fluctuate in time over a broad range of timescales (starting from daily weather changes, through seasonal alternations and decades-long host life-cycles, up to long-scale climate changes, to mention just a few). Our results[SzDV06] show that in the presence of weak inter-population migration NGT is able to subsist as a mechanism to reload locally lost, intermittently selected genes from the collective gene pool of the species through DNA uptake from migrants. Reloading genes and combining them with those in locally adapted genomes allow individual cells to readapt faster to environmental changes. The machinery of transformation survives under a wide range of model parameters readily encompassing real-world biological conditions. These findings imply that the primary role of NGT is not to serve the cell with food, but to provide homologous sequences for restoring genes that have disappeared from or become degraded in the local population. As our model system, we considered a bacterial species (a metapopulation) that is capable of living on 10 different types of food (Fig. 1a-b). We were able to take into account migration between the populations (a crucial element of the model, as without it NGT would just futilely reshuffle the existing genes inside the populations) very efficiently in terms of a mean field approach, commonly used in statistical physics. Performing extensive computer simulations for various values of the two main external parameters, the food change rate Rfood and the migration rate Rmigr , we found that NGT 1 Department of Biological Physics, Eötvös University, Budapest, Hungary of Genetics, Eötvös University, Budapest, Hungary E-mail: [email protected] 2 Department 2 15 !10" t abc ABCDEFGHIJ b t abh ABCDEFGHIJ t h t ah * * * t abh 10 10 0 10-9 10-1 10-10 10-2 Transformation survives 10-11 10-3 3 10 abc 10-5 ABCDEFGHIJ 10 5 10-8 10-12 ABCDEFGHIJ rrmax rrmax rt typical inux of bacteria, 108 X Rmigr [bacteria / hour] abc migration rate, Rmigr [hour- -1] 3 ln -7 10-4 1 / year 10-3 1 / month 10-2 0 b rm ln N 100 fraction of population (%) 3 rw ln N t gene 1 food 2 food 3 food 4 food 5 food 80 60 40 20 0.00001 0.0001 0.001 food change rate, Rfood [hour -1] fraction of population (%) !10" rm ln N ca *h * fraction of competent bacteria (%) a 1 / day food change rate, Rfood [hour -1] Figure 1: At any moment 3 out of 10 possible food sources are available, but their types change in time independently in each population of the metapopulation. At a common rate Rfood one of the food sources is randomly replaced by another one not currently available in the population. Bacteria reproduce at a rate that depends on the amount of available food they can utilize and decreases with the number of functional model food genes possessed. Bacteria can be washed out at a fixed rate , lose any of their functional genes by mutation, and those possessing a functional copy of the model gene for NGT may attempt to incorporate exogenous DNA into their genome. Food types are denoted by A, B, ... Individual bacteria can utilize any of these foods only if they have the corresponding model food gene (a, b, .., respectively) present in their genomes. The t gene responsible for DNA uptake can spread in two ways as local food types change from ABC to ABH: (a) Under rapidly changing conditions newly arrived bacteria with the h gene spread due to a lack of competition, allowing local bacteria capable of NGT (cells with perforation) to successfully adapt by assembling the optimal combination of model genes abh+t – in the process spreading the t gene. (b) Under slowly changing conditions, gene t often disappears from the local population. It is, however, possible that a competent bacterium possessing gene h arrives from another population and subsequently assembles the optimal gene combination abh+t. (c) The survival range of NGT based on stochastic simulations. The limits beyond which NGT cannot persist (dashed straight lines), either because the temporal or the spatial fluctuations become irrelevant, can be estimated analytically[SzDV06]. survives under a wide range of parameters(Fig. 1c). In these stochastic population dynamics simulations we numerically followed the time evolution of the number of bacteria in each of the possible 210+1 genotypes (representing the presence or absence of the 10 model food genes and the model transformation gene) in a single population. References [H98] Hanski, I. 1998. Metapopulation dynamics. Nature 396:41–49. [MOM01] Mira, A., Ochman, H. and Moran, N.A. 2001. Deletional bias and the evolution of bacterial genomes. Trends Genet. 17:589-596. [OL02] Otto, S.P. and Lenormand, T. 2002. Resolving the paradox of sex and recombination. Nat. Rev. Genet. 3:252–260. [R97] Redfield, J.R. et al. 1997. The evolution of bacterial transformation. Genetics 146:27-38. [SzDV06] Szöllősi, G.J., Derényi, I. and Vellai, T. 2006. The maintenance of sex in bacteria is ensured by its potential to reload genes. Genetics 174:2173–2108 100 100 80 80 60 60 40 40 20 20 0 50000 100000 150000 time [hour] 200000 0 50000 100000 150000 time [hour]