Transition from positive to neutral in mutation fixation along with continuing rising fitness in thermal adaptive evolution

Genomic diversity of "deep ecotype" Alteromonas macleodii isolates: evidence for Pan-Mediterranean clonal frames

We have compared genomes of Alteromonas macleodii “deep ecotype” isolates from two deep Mediterranean sites and two surface samples from the Aegean and the English Channel. A total of nine different genomes were analyzed. They belong to five clonal frames (CFs) that differ among them by approximately 30,000 single-nucleotide polymorphisms (SNPs) over their core genomes. Two of the CFs contain three strains each with nearly identical genomes (∼100 SNPs over the core genome). One of the CFs had representatives that were isolated from samples taken more than 1,000 km away, 2,500 m deeper, and 5 years apart. These data mark the longest proven persistence of a CF in nature (outside of clinical settings). We have found evidence for frequent recombination events between or within CFs and even with the distantly related A. macleodii surface ecotype. The different CFs had different flexible genomic islands. They can be classified into two groups; one type is additive, that is, containing different numbers of gene cassettes, and is very variable in short time periods (they often varied even within a single CF). The other type was more stable and produced the complete replacement of a genomic fragment by another with different genes. Although this type was more conserved within each CF, we found examples of recombination among distantly related CFs including English Channel and Mediterranean isolates.

Microbial evolution in vivo and in silico: methods and applications

Microbial evolution has been extensively studied in the past fifty years, which has lead to seminal discoveries that have shaped our understanding of evolutionary forces and dynamics. It is only recently however, that transformative technologies and computational advances have enabled a larger in-scale and in-depth investigation of the genetic basis and mechanistic underpinnings of evolutionary adaptation. In this review we focus on the strengths and limitations of in vivo and in silico techniques for studying microbial evolution in the laboratory, and we discuss how these complementary approaches can be integrated in a unifying framework for elucidating microbial evolution.

Emerging tools for synthetic genome design

Synthetic biology is an emerging discipline for designing and synthesizing predictable, measurable, controllable, and transformable biological systems. These newly designed biological systems have great potential for the development of cheaper drugs, green fuels, biodegradable plastics, and targeted cancer therapies over the coming years. Fortunately, our ability to quickly and accurately engineer biological systems that behave predictably has been dramatically expanded by significant advances in DNA-sequencing, DNA-synthesis, and DNA-editing technologies. Here, we review emerging technologies and methodologies in the field of building designed biological systems, and we discuss their future perspectives.

Multilevel comparative analysis of the contributions of genome reduction and heat shock to the Escherichia coli transcriptome

Background

Both large deletions in genome and heat shock stress would lead to alterations in the gene expression profile; however, whether there is any potential linkage between these disturbances to the transcriptome have not been discovered. Here, the relationship between the genomic and environmental contributions to the transcriptome was analyzed by comparing the transcriptomes of the bacterium Escherichia coli (strain MG1655 and its extensive genomic deletion derivative, MDS42) grown in regular and transient heat shock conditions.

Results

The transcriptome analysis showed the following: (i) there was a reorganization of the transcriptome in accordance with preferred chromosomal periodicity upon genomic or heat shock perturbation; (ii) there was a considerable overlap between the perturbed regulatory networks and the categories enriched for differentially expressed genes (DEGs) following genome reduction and heat shock; (iii) the genes sensitive to genome reduction tended to be located close to genomic scars, and some were also highly responsive to heat shock; and (iv) the genomic and environmental contributions to the transcriptome displayed not only a positive correlation but also a negatively compensated relationship (i.e., antagonistic epistasis).

Conclusion

The contributions of genome reduction and heat shock to the Escherichia coli transcriptome were evaluated at multiple levels. The observations of overlapping perturbed networks, directional similarity in transcriptional changes, positive correlation and epistatic nature linked the two contributions and suggest somehow a crosstalk guiding transcriptional reorganization in response to both genetic and environmental disturbances in bacterium E. coli.

Mutation accumulation and fitness in mutator subpopulations of Escherichia coli

Bacterial populations in clinical and laboratory settings contain a significant proportion of mutants with elevated mutation rates (mutators). Mutators have a particular advantage when multiple beneficial mutations are needed for fitness, as in antibiotic resistance. Nevertheless, high mutation rates potentially lead to increasing numbers of deleterious mutations and subsequently to the decreased fitness of mutators. To test how fitness changed with mutation accumulation, genome sequencing and fitness assays of nine Escherichia coli mutY mutators were undertaken in an evolving chemostat population at three time points. Unexpectedly, the fitness in members of the mutator subpopulation became constant despite a growing number of mutations over time. To test if the accumulated mutations affected fitness, we replaced each of the known beneficial mutations with wild-type alleles in a mutator isolate. We found that the other 25 accumulated mutations were not deleterious. Our results suggest that isolates with deleterious mutations are eliminated by competition in a continuous culture, leaving mutators with mostly neutral mutations. Interestingly, the mutator-non-mutator balance in the population reversed after the fitness plateau of mutators was reached, suggesting that the mutator-non-mutator ratio in populations has more to do with competition between members of the population than the accumulation of deleterious mutations.

Current understanding of the formation and adaptation of metabolic systems based on network theory

Formation and adaptation of metabolic networks has been a long-standing question in biology. With recent developments in biotechnology and bioinformatics, the understanding of metabolism is progressively becoming clearer from a network perspective. This review introduces the comprehensive metabolic world that has been revealed by a wide range of data analyses and theoretical studies; in particular, it illustrates the role of evolutionary events, such as gene duplication and horizontal gene transfer, and environmental factors, such as nutrient availability and growth conditions, in evolution of the metabolic network. Furthermore, the mathematical models for the formation and adaptation of metabolic networks have also been described, according to the current understanding from a perspective of metabolic networks. These recent findings are helpful in not only understanding the formation of metabolic networks and their adaptation, but also metabolic engineering.

Parallel genetic changes and nonparallel gene-environment interactions characterize the evolution of drug resistance in yeast

Beneficial mutations are required for adaptation to novel environments, yet the range of mutational pathways that are available to a population has been poorly characterized, particularly in eukaryotes. We assessed the genetic changes of the first mutations acquired during adaptation to a novel environment (exposure to the fungicide, nystatin) in 35 haploid lines of Saccharomyces cerevisiae. Through whole-genome resequencing we found that the genomic scope for adaptation was narrow; all adapted lines acquired a mutation in one of four late-acting genes in the ergosterol biosynthesis pathway, with very few other mutations found. Lines that acquired different ergosterol mutations in the same gene exhibited very similar tolerance to nystatin. All lines were found to have a cost relative to wild type in an unstressful environment; the level of this cost was also strongly correlated with the ergosterol gene bearing the mutation. Interestingly, we uncovered both positive and negative effects on tolerance to other harsh environments for mutations in the different ergosterol genes, indicating that these beneficial mutations have effects that differ in sign among environmental challenges. These results demonstrate that although the genomic target was narrow, different adaptive mutations can lead populations down different evolutionary pathways, with respect to their ability to tolerate (or succumb to) other environmental challenges.

Fitness landscape transformation through a single amino acid change in the rho terminator

Regulatory networks allow organisms to match adaptive behavior to the complex and dynamic contingencies of their native habitats. Upon a sudden transition to a novel environment, the mismatch between the native behavior and the new niche provides selective pressure for adaptive evolution through mutations in elements that control gene expression. In the case of core components of cellular regulation and metabolism, with broad control over diverse biological processes, such mutations may have substantial pleiotropic consequences. Through extensive phenotypic analyses, we have characterized the systems-level consequences of one such mutation (rho*) in the global transcriptional terminator Rho of Escherichia coli. We find that a single amino acid change in Rho results in a massive change in the fitness landscape of the cell, with widely discrepant fitness consequences of identical single locus perturbations in rho* versus rho^WT backgrounds. Our observations reveal the extent to which a single regulatory mutation can transform the entire fitness landscape of the cell, causing a massive change in the interpretation of individual mutations and altering the evolutionary trajectories which may be accessible to a bacterial population.

Bacteria rely on complex genetic regulatory networks to respond to hazards or opportunities that they encounter. These networks consist of a series of sensory modules, coupled with various response elements that must be appropriately activated to deal with a given set of environmental conditions; all of these condition-specific elements interact with the cell's core machinery for gene expression. When they encounter a novel environment, populations of bacteria rapidly evolve to adapt to that environment; alterations in gene expression play a major role in this process and, in particular, mutations to the cell's central gene expression machinery are surprisingly common in laboratory evolution experiments. Focusing on one such mutation that had previously been shown to enhance the host cell's ethanol tolerance, we show that the same alteration can in fact aid cellular survival under a wide variety of conditions. In addition, the interactions of this regulatory mutation with other genes throughout the genome cause these mutations to fundamentally reshape the effects of any other genomic changes that occur, and thus alter the overall evolutionary course taken by a population.

Genome features of "Dark-fly", a Drosophila line reared long-term in a dark environment

Organisms are remarkably adapted to diverse environments by specialized metabolisms, morphology, or behaviors. To address the molecular mechanisms underlying environmental adaptation, we have utilized a Drosophila melanogaster line, termed “Dark-fly”, which has been maintained in constant dark conditions for 57 years (1400 generations). We found that Dark-fly exhibited higher fecundity in dark than in light conditions, indicating that Dark-fly possesses some traits advantageous in darkness. Using next-generation sequencing technology, we determined the whole genome sequence of Dark-fly and identified approximately 220,000 single nucleotide polymorphisms (SNPs) and 4,700 insertions or deletions (InDels) in the Dark-fly genome compared to the genome of the Oregon-R-S strain, a control strain. 1.8% of SNPs were classified as non-synonymous SNPs (nsSNPs: i.e., they alter the amino acid sequence of gene products). Among them, we detected 28 nonsense mutations (i.e., they produce a stop codon in the protein sequence) in the Dark-fly genome. These included genes encoding an olfactory receptor and a light receptor. We also searched runs of homozygosity (ROH) regions as putative regions selected during the population history, and found 21 ROH regions in the Dark-fly genome. We identified 241 genes carrying nsSNPs or InDels in the ROH regions. These include a cluster of alpha-esterase genes that are involved in detoxification processes. Furthermore, analysis of structural variants in the Dark-fly genome showed the deletion of a gene related to fatty acid metabolism. Our results revealed unique features of the Dark-fly genome and provided a list of potential candidate genes involved in environmental adaptation.

The molecular diversity of adaptive convergence

To estimate the number and diversity of beneficial mutations, we experimentally evolved 115 populations of Escherichia coli to 42.2°C for 2000 generations and sequenced one genome from each population. We identified 1331 total mutations, affecting more than 600 different sites. Few mutations were shared among replicates, but a strong pattern of convergence emerged at the level of genes, operons, and functional complexes. Our experiment uncovered a set of primary functional targets of high temperature, but we estimate that many other beneficial mutations could contribute to similar adaptive outcomes. We inferred the pervasive presence of epistasis among beneficial mutations, which shaped adaptive trajectories into at least two distinct pathways involving mutations either in the RNA polymerase complex or the termination factor rho.

Evolutionary engineering for industrial microbiology

Superficially, evolutionary engineering is a paradoxical field that balances competing interests. In natural settings, evolution iteratively selects and enriches subpopulations that are best adapted to a particular ecological niche using random processes such as genetic mutation. In engineering desired approaches utilize rational prospective design to address targeted problems. When considering details of evolutionary and engineering processes, more commonality can be found. Engineering relies on detailed knowledge of the problem parameters and design properties in order to predict design outcomes that would be an optimized solution. When detailed knowledge of a system is lacking, engineers often employ algorithmic search strategies to identify empirical solutions. Evolution epitomizes this iterative optimization by continuously diversifying design options from a parental design, and then selecting the progeny designs that represent satisfactory solutions. In this chapter, the technique of applying the natural principles of evolution to engineer microbes for industrial applications is discussed to highlight the challenges and principles of evolutionary engineering.

Phenotypic plasticity and robustness: evolutionary stability theory, gene expression dynamics model, and laboratory experiments

Plasticity and robustness, which are two basic concepts in the evolution of developmental dynamics, are characterized in terms of the variance of phenotype distribution. Plasticity concerns the response of a phenotype against environmental and genetic changes, whereas robustness is the degree of insensitivity against such changes. Note that the sensitivity increases with the variance, and the inverse of the variance works as a measure of the robustness. First, it is found that the response ratio is proportional to the phenotype variance, as described by extending the fluctuation-response relationship in statistical physics. Next, it is shown that through the course of robust evolution, the phenotype variance caused by genetic change decreases in proportion to that by noise during the developmental process. This evolution, resulting in increased robustness, is achieved only when the noise in the developmental process is sufficiently large; in other words, robustness to noise leads to robustness to mutation. For a system that achieves robustness in the phenotype, it is also found that the proportionality between the two variances also holds across different phenotypic traits. These general relationships for plasticity and robustness in terms of fluctuations are demonstrated using macroscopic phenomenological theory, simulations of gene-expression dynamics models with regulation networks, and laboratory selection experiments. It is also shown that an optimal noise level compatibility between robustness and plasticity is achieved to cope with a fluctuating environment.

Quantifying selection acting on a complex trait using allele frequency time series data

When selection is acting on a large genetically diverse population, beneficial alleles increase in frequency. This fact can be used to map quantitative trait loci by sequencing the pooled DNA from the population at consecutive time points and observing allele frequency changes. Here, we present a population genetic method to analyze time series data of allele frequencies from such an experiment. Beginning with a range of proposed evolutionary scenarios, the method measures the consistency of each with the observed frequency changes. Evolutionary theory is utilized to formulate equations of motion for the allele frequencies, following which likelihoods for having observed the sequencing data under each scenario are derived. Comparison of these likelihoods gives an insight into the prevailing dynamics of the system under study. We illustrate the method by quantifying selective effects from an experiment, in which two phenotypically different yeast strains were first crossed and then propagated under heat stress (Parts L, Cubillos FA, Warringer J, et al. [14 co-authors]. 2011. Revealing the genetic structure of a trait by sequencing a population under selection. Genome Res). From these data, we discover that about 6% of polymorphic sites evolve nonneutrally under heat stress conditions, either because of their linkage to beneficial (driver) alleles or because they are drivers themselves. We further identify 44 genomic regions containing one or more candidate driver alleles, quantify their apparent selective advantage, obtain estimates of recombination rates within the regions, and show that the dynamics of the drivers display a strong signature of selection going beyond additive models. Our approach is applicable to study adaptation in a range of systems under different evolutionary pressures.

Ongoing phenotypic and genomic changes in experimental coevolution of RNA bacteriophage Qβ and Escherichia coli

According to the Red Queen hypothesis or arms race dynamics, coevolution drives continuous adaptation and counter-adaptation. Experimental models under simplified environments consisting of bacteria and bacteriophages have been used to analyze the ongoing process of coevolution, but the analysis of both parasites and their hosts in ongoing adaptation and counter-adaptation remained to be performed at the levels of population dynamics and molecular evolution to understand how the phenotypes and genotypes of coevolving parasite–host pairs change through the arms race. Copropagation experiments with Escherichia coli and the lytic RNA bacteriophage Qβ in a spatially unstructured environment revealed coexistence for 54 days (equivalent to 163–165 replication generations of Qβ) and fitness analysis indicated that they were in an arms race. E. coli first adapted by developing partial resistance to infection and later increasing specific growth rate. The phage counter-adapted by improving release efficiency with a change in host specificity and decrease in virulence. Whole-genome analysis indicated that the phage accumulated 7.5 mutations, mainly in the A2 gene, 3.4-fold faster than in Qβ propagated alone. E. coli showed fixation of two mutations (in traQ and csdA) faster than in sole E. coli experimental evolution. These observations suggest that the virus and its host can coexist in an evolutionary arms race, despite a difference in genome mutability (i.e., mutations per genome per replication) of approximately one to three orders of magnitude.

To examine the ongoing changes driven by host–parasite interactions, we have constructed a coevolution model consisting of Escherichia coli and the lytic RNA bacteriophage Qβ (Qβ) in a spatially unstructured environment. In coevolution through 54 daily copropagations of the parasite and its host, E. coli first evolved partial resistance to infection and later accelerated its specific growth rate, while the phage counter-adapted by improving release efficiency with a change in host specificity and a decrease in virulence. Whole-genome analysis of E. coli and Qβ revealed accelerated molecular evolution in comparison with Qβ propagation in this study and E. coli sole passage reported previously. The results of the present study indicated that, despite the large difference in mutability of their genomes (approximately one to three orders of magnitude difference), a host with larger genome size (4.6 Mbp) and a lower spontaneous mutation rate (5.4×10⁻¹⁰ per bp per replication) and a parasite with a smaller genome size (4,217 bases) and a higher mutation rate (1.5×10⁻³ to 1.5×10⁻⁵ per base per replication) were capable of changing their phenotypes to coexist in an arms race.

Mutation Rate Inferred From Synonymous Substitutions in a Long-Term Evolution Experiment With Escherichia coli

The quantification of spontaneous mutation rates is crucial for a mechanistic understanding of the evolutionary process. In bacteria, traditional estimates using experimental or comparative genetic methods are prone to statistical uncertainty and consequently estimates vary by over one order of magnitude. With the advent of next-generation sequencing, more accurate estimates are now possible. We sequenced 19 Escherichia coli genomes from a 40,000-generation evolution experiment and directly inferred the point-mutation rate based on the accumulation of synonymous substitutions. The resulting estimate was 8.9 × 10(-11) per base-pair per generation, and there was a significant bias toward increased AT-content. We also compared our results with published genome sequence datasets for other bacterial evolution experiments. Given the power of our approach, our estimate represents the most accurate measure of bacterial base-substitution rates available to date.

Microbial laboratory evolution in the era of genome-scale science

Advances in DNA sequencing, high-throughput technologies, and genetic manipulation systems have enabled empirical studies of the molecular and genomic bases of adaptive evolution. This review discusses key insights learned from direct observation of the evolution process.

Laboratory evolution studies provide fundamental biological insight through direct observation of the evolution process. They not only enable testing of evolutionary theory and principles, but also have applications to metabolic engineering and human health. Genome-scale tools are revolutionizing studies of laboratory evolution by providing complete determination of the genetic basis of adaptation and the changes in the organism's gene expression state. Here, we review studies centered on four central themes of laboratory evolution studies: (1) the genetic basis of adaptation; (2) the importance of mutations to genes that encode regulatory hubs; (3) the view of adaptive evolution as an optimization process; and (4) the dynamics with which laboratory populations evolve.