The fixation probability of rare mutators in finite asexual populations

A mutator is an allele that increases the mutation rate throughout the genome by disrupting some aspect of DNA replication or repair. Mutators that increase the mutation rate by the order of 100 fold have been observed to spontaneously emerge and achieve high frequencies in natural populations and in long-term laboratory evolution experiments with \textit{E. coli}. In principle, the fixation of mutator alleles is limited by (i) competition with mutations in wild-type backgrounds, (ii) additional deleterious mutational load, and (iii) random genetic drift. Using a multiple locus model and employing both simulation and analytic methods, we investigate the effects of these three factors on the fixation probability $P_{fix}$ of an initially rare mutator as a function of population size $N$, beneficial and deleterious mutation rates, and the strength of mutations $s$. Our diffusion based approximation for $P_{fix}$ successfully captures effects (ii) and (iii) when selection is fast compared to mutation ($\mu/s \ll 1$). This enables us to predict the conditions under which mutators will be evolutionarily favored. Surprisingly, our simulations show that effect (i) is typically small for strong-effect mutators. Our results agree semi-quantitatively with existing laboratory evolution experiments and suggest future experimental directions.Comment: 46 pages, 8 figure

The effects of low-impact mutations in digital organisms

<p>Abstract</p> <p>Background</p> <p>Avida is a computer program that performs evolution experiments with digital organisms. Previous work has used the program to study the evolutionary origin of complex features, namely logic operations, but has consistently used extremely large mutational fitness effects. The present study uses Avida to better understand the role of low-impact mutations in evolution.</p> <p>Results</p> <p>When mutational fitness effects were approximately 0.075 or less, no new logic operations evolved, and those that had previously evolved were lost. When fitness effects were approximately 0.2, only half of the operations evolved, reflecting a threshold for selection breakdown. In contrast, when Avida's default fitness effects were used, all operations routinely evolved to high frequencies and fitness increased by an average of 20 million in only 10,000 generations.</p> <p>Conclusions</p> <p>Avidian organisms evolve new logic operations only when mutations producing them are assigned high-impact fitness effects. Furthermore, purifying selection cannot protect operations with low-impact benefits from mutational deterioration. These results suggest that selection breaks down for low-impact mutations below a certain fitness effect, the <it>selection threshold</it>. Experiments using biologically relevant parameter settings show the tendency for increasing genetic load to lead to loss of biological functionality. An understanding of such genetic deterioration is relevant to human disease, and may be applicable to the control of pathogens by use of lethal mutagenesis.</p

Global divergence of microbial genome sequences mediated by propagating fronts

We model the competition between recombination and point mutation in microbial genomes, and present evidence for two distinct phases, one uniform, the other genetically diverse. Depending on the specifics of homologous recombination, we find that global sequence divergence can be mediated by fronts propagating along the genome, whose characteristic signature on genome structure is elucidated, and apparently observed in closely-related {\it Bacillus} strains. Front propagation provides an emergent, generic mechanism for microbial "speciation", and suggests a classification of microorganisms on the basis of their propensity to support propagating fronts

The Roots of Bioinformatics in Theoretical Biology

From the late 1980s onward, the term “bioinformatics” mostly has been used to refer to computational methods for comparative analysis of genome data. However, the term was originally more widely defined as the study of informatic processes in biotic systems. In this essay, I will trace this early history (from a personal point of view) and I will argue that the original meaning of the term is re-emerging

The genetic basis for adaptation of model-designed syntrophic co-cultures.

Understanding the fundamental characteristics of microbial communities could have far reaching implications for human health and applied biotechnology. Despite this, much is still unknown regarding the genetic basis and evolutionary strategies underlying the formation of viable synthetic communities. By pairing auxotrophic mutants in co-culture, it has been demonstrated that viable nascent E. coli communities can be established where the mutant strains are metabolically coupled. A novel algorithm, OptAux, was constructed to design 61 unique multi-knockout E. coli auxotrophic strains that require significant metabolite uptake to grow. These predicted knockouts included a diverse set of novel non-specific auxotrophs that result from inhibition of major biosynthetic subsystems. Three OptAux predicted non-specific auxotrophic strains-with diverse metabolic deficiencies-were co-cultured with an L-histidine auxotroph and optimized via adaptive laboratory evolution (ALE). Time-course sequencing revealed the genetic changes employed by each strain to achieve higher community growth rates and provided insight into mechanisms for adapting to the syntrophic niche. A community model of metabolism and gene expression was utilized to predict the relative community composition and fundamental characteristics of the evolved communities. This work presents new insight into the genetic strategies underlying viable nascent community formation and a cutting-edge computational method to elucidate metabolic changes that empower the creation of cooperative communities

Species-Specific Codon Context Rules Unveil Non-Neutrality Effects of Synonymous Mutations

Codon pair usage (codon context) is a species specific gene primary structure feature whose evolutionary and functional roles are poorly understood. The data available show that codon-context has direct impact on both translation accuracy and efficiency, but one does not yet understand how it affects these two translation variables or whether context biases shape gene evolution.Here we study codon-context biases using a set of 72 orthologous highly conserved genes from bacteria, archaea, fungi and high eukaryotes to identify 7 distinct groups of codon context rules. We show that synonymous mutations, i.e., neutral mutations that occur in synonymous codons of codon-pairs, are selected to maintain context biases and that non-synonymous mutations, i.e., non-neutral mutations that alter protein amino acid sequences, are also under selective pressure to preserve codon-context biases.Since in vivo studies provide evidence for a role of codon context on decoding fidelity in E. coli and for decoding efficiency in mammalian cells, our data support the hypothesis that, like codon usage, codon context modulates the evolution of gene primary structure and fine tunes the structure of open reading frames for high genome translational fidelity and efficiency in the 3 domains of life