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      Historical contingency and its biophysical basis in glucocorticoid receptor evolution

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      1 , 3 , 2 , 3
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          Abstract

          Understanding how chance historical events shape evolutionary processes is a central goal of evolutionary biology 17 . Direct insights into the extent and causes of evolutionary contingency have been limited to experimental systems, 79 because it is difficult to know what happened in the deep past and to characterize other paths that evolution could have followed. Here we combine ancestral protein reconstruction, directed evolution, and biophysical analysis to explore alternate “might-have-been” trajectories during the ancient evolution of a novel protein function. We previously found that the evolution of cortisol specificity in the ancestral glucocorticoid receptor (GR) was contingent on permissive substitutions, which had no apparent effect on receptor function but were necessary for GR to tolerate the large-effect mutations that caused the shift in specificity. 6 Here we show that alternative mutations that could have permitted the historical function-switching substitutions are extremely rare in the ensemble of genotypes accessible to the ancestral GR. In a library of thousands of variants of the ancestral protein, we recovered historical permissive substitutions, but no alternate permissive genotypes. Using biophysical analysis, we found that permissive mutations must satisfy at least three physical requirements—they must stabilize specific local elements of the protein structure, maintain the correct energetic balance between functional conformations, and be compatible with the ancestral and derived structures—thus revealing why permissive mutations are rare. These findings demonstrate that GR evolution depended strongly on improbable, nondeterministic events, and this contingency arose from intrinsic biophysical properties of the protein.

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          Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli.

          The role of historical contingency in evolution has been much debated, but rarely tested. Twelve initially identical populations of Escherichia coli were founded in 1988 to investigate this issue. They have since evolved in a glucose-limited medium that also contains citrate, which E. coli cannot use as a carbon source under oxic conditions. No population evolved the capacity to exploit citrate for >30,000 generations, although each population tested billions of mutations. A citrate-using (Cit+) variant finally evolved in one population by 31,500 generations, causing an increase in population size and diversity. The long-delayed and unique evolution of this function might indicate the involvement of some extremely rare mutation. Alternately, it may involve an ordinary mutation, but one whose physical occurrence or phenotypic expression is contingent on prior mutations in that population. We tested these hypotheses in experiments that "replayed" evolution from different points in that population's history. We observed no Cit+ mutants among 8.4 x 10(12) ancestral cells, nor among 9 x 10(12) cells from 60 clones sampled in the first 15,000 generations. However, we observed a significantly greater tendency for later clones to evolve Cit+, indicating that some potentiating mutation arose by 20,000 generations. This potentiating change increased the mutation rate to Cit+ but did not cause generalized hypermutability. Thus, the evolution of this phenotype was contingent on the particular history of that population. More generally, we suggest that historical contingency is especially important when it facilitates the evolution of key innovations that are not easily evolved by gradual, cumulative selection.
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            Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models.

            CHARMM27 is a widespread and popular force field for biomolecular simulation, and several recent algorithms such as implicit solvent models have been developed specifically for it. We have here implemented the CHARMM force field and all necessary extended functional forms in the GROMACS molecular simulation package, to make CHARMM-specific features available and to test them in combination with techniques for extended time steps, to make all major force fields available for comparison studies in GROMACS, and to test various solvent model optimizations, in particular the effect of Lennard-Jones interactions on hydrogens. The implementation has full support both for CHARMM-specific features such as multiple potentials over the same dihedral angle and the grid-based energy correction map on the ϕ, ψ protein backbone dihedrals, as well as all GROMACS features such as virtual hydrogen interaction sites that enable 5 fs time steps. The medium-to-long time effects of both the correction maps and virtual sites have been tested by performing a series of 100 ns simulations using different models for water representation, including comparisons between CHARMM and traditional TIP3P. Including the correction maps improves sampling of near native-state conformations in our systems, and to some extent it is even able to refine distorted protein conformations. Finally, we show that this accuracy is largely maintained with a new implicit solvent implementation that works with virtual interaction sites, which enables performance in excess of 250 ns/day for a 900-atom protein on a quad-core desktop computer.
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              Bias in template-to-product ratios in multitemplate PCR.

              Bias introduced by the simultaneous amplification of specific genes from complex mixtures of templates remains poorly understood. To explore potential causes and the extent of bias in PCR amplification of 16S ribosomal DNAs (rDNAs), genomic DNAs of two closely and one distantly related bacterial species were mixed and amplified with universal, degenerate primers. Quantification and comparison of template and product ratios showed that there was considerable and reproducible overamplification of specific templates. Variability between replicates also contributed to the observed bias but in a comparatively minor way. Based on these initial observations, template dosage and differences in binding energies of permutations of the degenerate, universal primers were tested as two likely causes of this template-specific bias by using 16S rDNA templates modified by site-directed mutagenesis. When mixtures of mutagenized templates containing AT- and GC-rich priming sites were used, templates containing the GC-rich permutation amplified with higher efficiency, indicating that different primer binding energies may to a large extent be responsible for overamplification. In contrast, gene copy number was found to be an unlikely cause of the observed bias. Similarly, amplification from DNA extracted from a natural community to which different amounts of genomic DNA of a single bacterial species were added did not affect relative product ratios. Bias was reduced considerably by using high template concentrations, by performing fewer cycles, and by mixing replicate reaction preparations.

                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                6 May 2015
                15 June 2014
                14 August 2014
                28 May 2015
                : 512
                : 7513
                : 203-207
                Affiliations
                [1 ]Institute of Molecular Biology & Department of Chemistry, University of Oregon, Eugene, OR 97403 USA
                [2 ]Departments of Human Genetics and Ecology & Evolution, University of Chicago, Chicago IL 60637 USA
                [3 ]Institute of Ecology and Evolution, University of Oregon, Eugene, OR 97403 USA
                Author notes
                Correspondence to: Joe Thornton, joet1@ 123456uchicago.edu
                Article
                NIHMS590618
                10.1038/nature13410
                4447330
                24930765
                6d7e519d-76f3-4405-bd6c-aa9c69a266c5
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