Molecular automata that combine sensing, computation and actuation enable programmable manipulation of biological systems. We use RNA interference (RNAi) in human kidney cells to construct a molecular computing core that implements general Boolean logic to make decisions based on endogenous molecular inputs. The state of an endogenous input is encoded by the presence or absence of 'mediator' small interfering RNAs (siRNAs). The encoding rules, combined with a specific arrangement of the siRNA targets in a synthetic gene network, allow direct evaluation of any Boolean expression in standard forms using siRNAs and indirect evaluation using endogenous inputs. We demonstrate direct evaluation of expressions with up to five logic variables. Implementation of the encoding rules through sensory up- and down-regulatory links between the inputs and siRNA mediators will allow arbitrary Boolean decision-making using these inputs.
Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.
Twelve replicate populations of Escherichia coli have been evolving in the laboratory for .25 years and 60,000 generations. We analyzed bacteria from whole-population samples frozen every 500 generations through 20,000 generations for one wellstudied population, called Ara21. By tracking 42 known mutations in these samples, we reconstructed the history of this population's genotypic evolution over this period. The evolutionary dynamics of Ara21 show strong evidence of selective sweeps as well as clonal interference between competing lineages bearing different beneficial mutations. In some cases, sets of several mutations approached fixation simultaneously, often conveying no information about their order of origination; we present several possible explanations for the existence of these mutational cohorts. Against a backdrop of rapid selective sweeps both earlier and later, two genetically diverged clades coexisted for .6000 generations before one went extinct. In that time, many additional mutations arose in the clade that eventually prevailed. We show that the clades evolved a frequency-dependent interaction, which prevented the immediate competitive exclusion of either clade, but which collapsed as beneficial mutations accumulated in the clade that prevailed. Clonal interference and frequency dependence can occur even in the simplest microbial populations. Furthermore, frequency dependence may generate dynamics that extend the period of coexistence that would otherwise be sustained by clonal interference alone.KEYWORDS experimental evolution; clonal interference; frequency-dependent selection; beneficial mutations; asexual populations; mutational cohorts T HE long-term evolution experiment (LTEE) spans .25 years and 60,000 generations of bacterial evolution. In this experiment, 12 replicate populations of Escherichia coli have been propagated in a simple environment, and samples of each population have been frozen at 500-generation intervals. This experiment originally focused on whether and to what extent the populations would diverge in their mean fitness and other phenotypic properties as they adapted to identical environments (Lenski et al. 1991;Lenski and Travisano 1994). Over time, this experiment has become a model for exploring many other aspects of evolution, including the emergence of new functions (Blount et al. 2008), the evolution of mutation rates (Sniegowski et al. 1997), the maintenance of genetic diversity (Elena and Lenski 1997;Rozen and Lenski 2000;Le Gac et al. 2012), and the structure of the fitness landscape (Khan et al. 2011;Woods et al. 2011;Wiser et al. 2013). The ability to examine these and other issues has grown tremendously as data that were difficult or impossible to obtain when the LTEE began have yielded to new technologies, particularly genome sequencing Lenski 2009, 2013;Blount et al. 2012;Wielgoss et al. 2013).The LTEE has also inspired theoretical work, especially on the dynamics of adaptation in large asexual populations (Gerrish and Lenski 1998;Hegreness et al....
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