Primary and promiscuous functions coexist during evolutionary innovation through whole protein domain acquisitions.

Molecular examples of evolutionary innovation are scarce and generally involve point mutations. Innovation can occur through larger rearrangements, but here experimental data is extremely limited. Integron integrases innovated from double-strand- toward single-strand-DNA recombination through the acquisition of the I2 α-helix. To investigate how this transition was possible, we have evolved integrase IntI1 to what should correspond to an early innovation state by selecting for its ancestral activity. Using synonymous alleles to enlarge sequence space exploration, we have retrieved 13 mutations affecting both I2 and the multimerization domains of IntI1. We circumvented epistasis constraints among them using a combinatorial library that revealed their individual and collective fitness effects. We obtained up to 104-fold increases in ancestral activity with various asymmetrical trade-offs in single-strand-DNA recombination. We show that high levels of primary and promiscuous functions could have initially coexisted following I2 acquisition, paving the way for a gradual evolution toward innovation.

Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway.

Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.

Recent insights into the genotype-phenotype relationship from massively parallel genetic assays.

With the molecular revolution in Biology, a mechanistic understanding of the genotype-phenotype relationship became possible. Recently, advances in DNA synthesis and sequencing have enabled the development of deep mutational scanning assays, capable of scoring comprehensive libraries of genotypes for fitness and a variety of phenotypes in massively parallel fashion. The resulting empirical genotype-fitness maps pave the way to predictive models, potentially accelerating our ability to anticipate the behaviour of pathogen and cancerous cell populations from sequencing data. Besides from cellular fitness, phenotypes of direct application in industry (e.g. enzyme activity) and medicine (e.g. antibody binding) can be quantified and even selected directly by these assays. This review discusses the technological basis of and recent developments in massively parallel genetics, along with the trends it is uncovering in the genotype-phenotype relationship (distribution of mutation effects, epistasis), their possible mechanistic bases and future directions for advancing towards the goal of predictive genetics.

Advantage of the F2:A1:B- IncF Pandemic Plasmid over IncC Plasmids in In Vitro Acquisition and Evolution of blaCTX-M Gene-Bearing Plasmids in Escherichia coli.

Despite a fitness cost imposed on bacterial hosts, large conjugative plasmids play a key role in the diffusion of resistance determinants, such as CTX-M extended-spectrum ß-lactamases. Among the large conjugative plasmids, IncF plasmids are the most predominant group, and an F2:A1:B- IncF-type plasmid encoding a CTX-M-15 variant was recently described as being strongly associated with the emerging worldwide Escherichia coli sequence type 131 (ST131)-O25b:H4 H30Rx/C2 sublineage. In this context, we investigated the fitness cost of narrow-range F-type plasmids, including the F2:A1:B- IncF-type CTX-M-15 plasmid, and of broad-range C-type plasmids in the K-12-like J53-2 E. coli strain. Although all plasmids imposed a significant fitness cost to the bacterial host immediately after conjugation, we show, using an experimental-evolution approach, that a negative impact on the fitness of the host strain was maintained throughout 1,120 generations with the IncC-IncR plasmid, regardless of the presence or absence of cefotaxime, in contrast to the F2:A1:B- IncF plasmid, whose cost was alleviated. Many chromosomal and plasmid rearrangements were detected after conjugation in transconjugants carrying the IncC plasmids but not in transconjugants carrying the F2:A1:B- IncF plasmid, except for insertion sequence (IS) mobilization from the fliM gene leading to the restoration of motility of the recipient strains. Only a few mutations occurred on the chromosome of each transconjugant throughout the experimental-evolution assay. Our findings indicate that the F2:A1:B- IncF CTX-M-15 plasmid is well adapted to the E. coli strain studied, contrary to the IncC-IncR CTX-M-15 plasmid, and that such plasmid-host adaptation could participate in the evolutionary success of the CTX-M-15-producing pandemic E. coli ST131-O25b:H4 lineage.

A checkpoint control orchestrates the replication of the two chromosomes of Vibrio cholerae.

Bacteria with multiple chromosomes represent up to 10% of all bacterial species. Unlike eukaryotes, these bacteria use chromosome-specific initiators for their replication. In all cases investigated, the machineries for secondary chromosome replication initiation are of plasmid origin. One of the important differences between plasmids and chromosomes is that the latter replicate during a defined period of the cell cycle, ensuring a single round of replication per cell. Vibrio cholerae carries two circular chromosomes, Chr1 and Chr2, which are replicated in a well-orchestrated manner with the cell cycle and coordinated in such a way that replication termination occurs at the same time. However, the mechanism coordinating this synchrony remains speculative. We investigated this mechanism and revealed that initiation of Chr2 replication is triggered by the replication of a 150-bp locus positioned on Chr1, called crtS. This crtS replication-mediated Chr2 replication initiation mechanism explains how the two chromosomes communicate to coordinate their replication. Our study reveals a new checkpoint control mechanism in bacteria, and highlights possible functional interactions mediated by contacts between two chromosomes, an unprecedented observation in bacteria.

Prebiotic network evolution: six key parameters.

The origins of life likely required the cooperation among a set of molecular species interacting in a network. If so, then the earliest modes of evolutionary change would have been governed by the manners and mechanisms by which networks change their compositions over time. For molecular events, especially those in a pre-biological setting, these mechanisms have rarely been considered. We are only recently learning to apply the results of mathematical analyses of network dynamics to prebiotic events. Here, we attempt to forge connections between such analyses and the current state of knowledge in prebiotic chemistry. Of the many possible influences that could direct primordial network, six parameters emerge as the most influential when one considers the molecular characteristics of the best candidates for the emergence of biological information: polypeptides, RNA-like polymers, and lipids. These parameters are viable cores, connectivity kinetics, information control, scalability, resource availability, and compartmentalization. These parameters, both individually and jointly, guide the aggregate evolution of collectively autocatalytic sets. We are now in a position to translate these conclusions into a laboratory setting and test empirically the dynamics of prebiotic network evolution.