A microbial model of economic trading and comparative advantage.

The economic theory of comparative advantage postulates that beneficial trading relationships can be arrived at by two self-interested entities producing the same goods as long as they have opposing relative efficiencies in producing those goods. The theory predicts that upon entering trade, in order to maximize consumption both entities will specialize in producing the good they can produce at higher efficiency, that the weaker entity will specialize more completely than the stronger entity, and that both will be able to consume more goods as a result of trade than either would be able to alone. We extend this theory to the realm of unicellular organisms by developing mathematical models of genetic circuits that allow trading of a common good (specifically, signaling molecules) required for growth in bacteria in order to demonstrate comparative advantage interactions. In Conception 1, the experimenter controls production rates via exogenous inducers, allowing exploration of the parameter space of specialization. In Conception 2, the circuits self-regulate via feedback mechanisms. Our models indicate that these genetic circuits can demonstrate comparative advantage, and that cooperation in such a manner is particularly favored under stringent external conditions and when the cost of production is not overly high. Further work could involve implementing the models in living bacteria and searching for naturally occurring cooperative relationships between bacteria that conform to the principles of comparative advantage.

Generalized bacterial genome editing using mobile group II introns and Cre-lox.

Efficient bacterial genetic engineering approaches with broad-host applicability are rare. We combine two systems, mobile group II introns ('targetrons') and Cre/lox, which function efficiently in many different organisms, into a versatile platform we call GETR (Genome Editing via Targetrons and Recombinases). The introns deliver lox sites to specific genomic loci, enabling genomic manipulations. Efficiency is enhanced by adding flexibility to the RNA hairpins formed by the lox sites. We use the system for insertions, deletions, inversions, and one-step cut-and-paste operations. We demonstrate insertion of a 12-kb polyketide synthase operon into the lacZ gene of Escherichia coli, multiple simultaneous and sequential deletions of up to 120 kb in E. coli and Staphylococcus aureus, inversions of up to 1.2 Mb in E. coli and Bacillus subtilis, and one-step cut-and-pastes for translocating 120 kb of genomic sequence to a site 1.5 Mb away. We also demonstrate the simultaneous delivery of lox sites into multiple loci in the Shewanella oneidensis genome. No selectable markers need to be placed in the genome, and the efficiency of Cre-mediated manipulations typically approaches 100%.

Biotechnological applications of mobile group II introns and their reverse transcriptases: gene targeting, RNA-seq, and non-coding RNA analysis.

Mobile group II introns are bacterial retrotransposons that combine the activities of an autocatalytic intron RNA (a ribozyme) and an intron-encoded reverse transcriptase to insert site-specifically into DNA. They recognize DNA target sites largely by base pairing of sequences within the intron RNA and achieve high DNA target specificity by using the ribozyme active site to couple correct base pairing to RNA-catalyzed intron integration. Algorithms have been developed to program the DNA target site specificity of several mobile group II introns, allowing them to be made into 'targetrons.' Targetrons function for gene targeting in a wide variety of bacteria and typically integrate at efficiencies high enough to be screened easily by colony PCR, without the need for selectable markers. Targetrons have found wide application in microbiological research, enabling gene targeting and genetic engineering of bacteria that had been intractable to other methods. Recently, a thermostable targetron has been developed for use in bacterial thermophiles, and new methods have been developed for using targetrons to position recombinase recognition sites, enabling large-scale genome-editing operations, such as deletions, inversions, insertions, and 'cut-and-pastes' (that is, translocation of large DNA segments), in a wide range of bacteria at high efficiency. Using targetrons in eukaryotes presents challenges due to the difficulties of nuclear localization and sub-optimal magnesium concentrations, although supplementation with magnesium can increase integration efficiency, and directed evolution is being employed to overcome these barriers. Finally, spurred by new methods for expressing group II intron reverse transcriptases that yield large amounts of highly active protein, thermostable group II intron reverse transcriptases from bacterial thermophiles are being used as research tools for a variety of applications, including qRT-PCR and next-generation RNA sequencing (RNA-seq). The high processivity and fidelity of group II intron reverse transcriptases along with their novel template-switching activity, which can directly link RNA-seq adaptor sequences to cDNAs during reverse transcription, open new approaches for RNA-seq and the identification and profiling of non-coding RNAs, with potentially wide applications in research and biotechnology.

Detecting clusters of mutations.

Positive selection for protein function can lead to multiple mutations within a small stretch of DNA, i.e., to a cluster of mutations. Recently, Wagner proposed a method to detect such mutation clusters. His method, however, did not take into account that residues with high solvent accessibility are inherently more variable than residues with low solvent accessibility. Here, we propose a new algorithm to detect clustered evolution. Our algorithm controls for different substitution probabilities at buried and exposed sites in the tertiary protein structure, and uses random permutations to calculate accurate P values for inferred clusters. We apply the algorithm to genomes of bacteria, fly, and mammals, and find several clusters of mutations in functionally important regions of proteins. Surprisingly, clustered evolution is a relatively rare phenomenon. Only between 2% and 10% of the genes we analyze contain a statistically significant mutation cluster. We also find that not controlling for solvent accessibility leads to an excess of clusters in terminal and solvent-exposed regions of proteins. Our algorithm provides a novel method to identify functionally relevant divergence between groups of species. Moreover, it could also be useful to detect artifacts in automatically assembled genomes.