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      Evolution of increased complexity in a molecular machine

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          Many cellular processes are carried out by molecular 'machines'-assemblies of multiple differentiated proteins that physically interact to execute biological functions. Despite much speculation, strong evidence of the mechanisms by which these assemblies evolved is lacking. Here we use ancestral gene resurrection and manipulative genetic experiments to determine how the complexity of an essential molecular machine--the hexameric transmembrane ring of the eukaryotic V-ATPase proton pump--increased hundreds of millions of years ago. We show that the ring of Fungi, which is composed of three paralogous proteins, evolved from a more ancient two-paralogue complex because of a gene duplication that was followed by loss in each daughter copy of specific interfaces by which it interacts with other ring proteins. These losses were complementary, so both copies became obligate components with restricted spatial roles in the complex. Reintroducing a single historical mutation from each paralogue lineage into the resurrected ancestral proteins is sufficient to recapitulate their asymmetric degeneration and trigger the requirement for the more elaborate three-component ring. Our experiments show that increased complexity in an essential molecular machine evolved because of simple, high-probability evolutionary processes, without the apparent evolution of novel functions. They point to a plausible mechanism for the evolution of complexity in other multi-paralogue protein complexes.

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          Most cited references 43

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

           Robert Edgar (2004)
          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice

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              A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood.

              The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximum- likelihood principle, which clearly satisfies these requirements. The core of this method is a simple hill-climbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distance-based method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximum-likelihood programs and much higher than the performance of distance-based and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximum-likelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distance-based and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page:

                Author and article information

                Springer Science and Business Media LLC
                January 2012
                January 9 2012
                January 2012
                : 481
                : 7381
                : 360-364
                © 2012



                added an editorial note to Evolutionary Cell Biology

                Multi-protein molecular machines are often surprisingly complex, and it is often assumed- and argued- that this complexity must be adaptive. Since complex interactions do not appear instantaneously this also raises a paradox because most mutations are either neutral or have deleterious effects on fitness. Alternatives to the adaptationist argument that can resolve this paradox, such as the theory of constructive neutral evolution (CNE), have existed for decades but are not widely discussed outside of the evolutionary biology community. The authors here use ancestral reconstruction and functional studies to provide actual experimental support for the CNE model. 

                They show that the ring of the fungal V-ATPase proton pump, a hexamer composed of three different paralogues, evolved from a simpler 2 paralogue version through a duplication followed by a series of high-likelihood mutations that degraded interactions with other ring proteins. These made the duplicated proteins dependent on each other, leading to an almost-irreversible increase in complexity (a "neutral evolutionary ratchet"). 

                See also Doolittle's news & views article on the paper. 

                More on CNE and neutral ratchets here: 
                How a neutral evolutionary ratchet can build evolutionary complexity 




                2016-04-20 14:56 UTC

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