Probabilistic reconstruction of ancestral protein sequences

Using a maximum-likelihood formalism, we have developed a method with which to reconstruct the sequences of ancestral proteins. Our approach allows the calculation of not only the most probable ancestral sequence but also of the probability of any amino acid at any given node in the evolutionary tree. Because we consider evolution on the amino acid level, we are better able to include effects of evolutionary pressure and take advantage of structural information about the protein through the use of mutation matrices that depend on secondary structure and surface accessibility. The computational complexity of this method scales linearly with the number of homologous proteins used to reconstruct the ancestral sequence.     

Analysis on the reconstruction accuracy of the Fitch method for inferring ancestral states

Background  

As one of the most widely used parsimony methods for ancestral reconstruction, the Fitch method minimizes the total number of hypothetical substitutions along all branches of a tree to explain the evolution of a character. Due to the extensive usage of this method, it has become a scientific endeavor in recent years to study the reconstruction accuracies of the Fitch method. However, most studies are restricted to 2-state evolutionary models and a study for higher-state models is needed since DNA sequences take the format of 4-state series and protein sequences even have 20 states.     

Evolution of protein specificity: insights from ancestral protein reconstruction

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Testing the accuracy of methods for reconstructing ancestral states of continuous characters.

Many methods are available for estimating ancestral values of continuous characteristics, but little is known about how well these methods perform. Here we compare six methods: linear parsimony, squared-change parsimony, one-parameter maximum likelihood (Brownian motion), two-parameter maximum likelihood (Ornstein-Uhlenbeck process), and independent comparisons with and without branch-length information. We apply these methods to data from 20 morphospecies of Pleistocene planktic Foraminifera in order to estimate ancestral size and shape variables, and compare these estimates with measurements on fossils close to the phylogenetic position of 13 ancestors. No method produced accurate estimates for any variable: estimates were consistently less good as predictors of the observed values than were the averages of the observed values. The two-parameter maximum-likelihood model consistently produces the most accurate size estimates overall. Estimation of ancestral sizes is confounded by an evolutionary trend towards increasing size. Shape showed no trend but was still estimated very poorly: we consider possible reasons. We discuss the implications of our results for the use of estimates of ancestral characteristics.     

Construction of a robust and sensitive arginine biosensor through ancestral protein reconstruction

Biosensors for signaling molecules allow the study of physiological processes by bringing together the fields of protein engineering, fluorescence imaging, and cell biology. Construction of genetically encoded biosensors generally relies on the availability of a binding “core” that is both specific and stable, which can then be combined with fluorescent molecules to create a sensor. However, binding proteins with the desired properties are often not available in nature and substantial improvement to sensors can be required, particularly with regard to their durability. Ancestral protein reconstruction is a powerful protein-engineering tool able to generate highly stable and functional proteins. In this work, we sought to establish the utility of ancestral protein reconstruction to biosensor development, beginning with the construction of an l-arginine biosensor. l-arginine, as the immediate precursor to nitric oxide, is an important molecule in many physiological contexts including brain function. Using a combination of ancestral reconstruction and circular permutation, we constructed a Förster resonance energy transfer (FRET) biosensor for l-arginine (cpFLIPR). cpFLIPR displays high sensitivity and specificity, with a K_d of ∼14 µM and a maximal dynamic range of 35%. Importantly, cpFLIPR was highly robust, enabling accurate l-arginine measurement at physiological temperatures. We established that cpFLIPR is compatible with two-photon excitation fluorescence microscopy and report l-arginine concentrations in brain tissue.     

A comparative study in ancestral range reconstruction methods: retracing the uncertain histories of insular lineages

Island systems have long been useful models for understanding lineage diversification in a geographic context, especially pertaining to the importance of dispersal in the origin of new clades. Here we use a well-resolved phylogeny of the flowering plant genus Cyrtandra (Gesneriaceae) from the Pacific Islands to compare four methods of inferring ancestral geographic ranges in islands: two developed for character-state reconstruction that allow only single-island ranges and do not explicitly associate speciation with range evolution (Fitch parsimony [FP; parsimony-based] and stochastic mapping [SM; likelihood-based]) and two methods developed specifically for ancestral range reconstruction, in which widespread ranges (spanning islands) are integral to inferences about speciation scenarios (dispersal-vicariance analysis [DIVA; parsimony-based] and dispersal-extinction-cladogenesis [DEC; likelihood-based]). The methods yield conflicting results, which we interpret in light of their respective assumptions. FP exhibits the least power to unequivocally reconstruct ranges, likely due to a combination of having flat (uninformative) transition costs and not using branch length information. SM reconstructions generally agree with a prior hypothesis about dispersal-driven speciation across the Pacific, despite the conceptual mismatch between its character-based model and this mode of range evolution. In contrast with narrow extant ranges for species of Cyrtandra, DIVA reconstructs broad ancestral ranges at many nodes. DIVA results also conflict with geological information on island ages; we attribute these conflicts to the parsimony criterion not considering branch lengths or time, as well as vicariance being the sole means of divergence for widespread ancestors. DEC analyses incorporated geological information on island ages and allowed prior hypotheses about range size and dispersal rates to be evaluated in a likelihood framework and gave more nuanced inferences about range evolution and the geography of speciation than other methods tested. However, ancestral ranges at several nodes could not be conclusively resolved, due possibly to uncertainty in the phylogeny or the relative complexity of the underlying model. Of the methods tested, SM and DEC both converge on plausible hypotheses for area range histories in Cyrtandra, due in part to the consideration of branch lengths and/or timing of events. We suggest that DEC model-based methods for ancestral range inference could be improved by adopting a Bayesian SM approach, in which stochastic sampling of complete geographic histories could be integrated over alternative phylogenetic topologies. Likelihood-based estimates of ancestral ranges for Cyrtandra suggest a major dispersal route into the Pacific through the islands of Fiji and Samoa, motivating future biogeographic investigation of this poorly known region.     

Towards the reconstruction of the bilaterian ancestral pre-MHC region

In this article, we describe how we reconstructed a precise, minimal proto-MHC region in the ancestor of euchordates, which was based on a comparison of the MHC-paralogy group of vertebrate with the MHC-like chromosome of cephalochordates. This deduced ancestral region was compared with the genomes of extant species, other deuterostomes and protostomes. Our analysis revealed statistically significant traces of conservation in these species, suggesting that a proto-MHC region existed at the origin of all bilaterian species. We also propose a new approach to reconstruct ancestral genomes, which combines both stringent statistical testing and phylogenetic analysis.     

Optimized ancestral state reconstruction using Sankoff parsimony

Background  

Parsimony methods are widely used in molecular evolution to estimate the most plausible phylogeny for a set of characters. Sankoff parsimony determines the minimum number of changes required in a given phylogeny when a cost is associated to transitions between character states. Although optimizations exist to reduce the computations in the number of taxa, the original algorithm takes time O(n ²) in the number of states, making it impractical for large values of n.     

酶祖先序列重建与定向进化

酶祖先序列重建是指通过计算机算法推导来自灭绝生物的祖先酶的氨基酸序列的技术.通常可分为6个步骤,依次为现代酶的核酸/氨基酸序列收集、多序列比对、系统发育树构建、祖先酶序列的计算机推测、基因克隆、酶学性质表征.该方法广泛应用于研究分子在行星时间尺度上对环境条件不断变化的适应性和进化机制.随着酶在生物催化领域中扮演越来越重...     

Comparison of protein phylogeny reconstruction methods using natural protein sequences

Comparison of several protein phylogeny reconstruction methods was realized on a set of natural protein sequences. The programs of the PHYLIP package and FastME, PhyML and TreeTop programs were tested. In contrast to several studied programs that used simulated sequences, our results demonstrate the superiority of distance methods over the maximum likelihood method.     

Strong functional patterns in the evolution of eukaryotic genomes revealed by the reconstruction of ancestral protein domain repertoires

Background  

Genome size and complexity, as measured by the number of genes or protein domains, is remarkably similar in most extant eukaryotes and generally exhibits no correlation with their morphological complexity. Underlying trends in the evolution of the functional content and capabilities of different eukaryotic genomes might be hidden by simultaneous gains and losses of genes.     

Comparative accuracy of methods for protein sequence similarity search

MOTIVATION: Searching a protein sequence database for homologs is a powerful tool for discovering the structure and function of a sequence. Two new methods for searching sequence databases have recently been described: Probabilistic Smith-Waterman (PSW), which is based on Hidden Markov models for a single sequence using a standard scoring matrix, and a new version of BLAST (WU-BLAST2), which uses Sum statistics for gapped alignments. RESULTS: This paper compares and contrasts the effectiveness of these methods with three older methods (Smith- Waterman: SSEARCH, FASTA and BLASTP). The analysis indicates that the new methods are useful, and often offer improved accuracy. These tools are compared using a curated (by Bill Pearson) version of the annotated portion of PIR 39. Three different statistical criteria are utilized: equivalence number, minimum errors and the receiver operating characteristic. For complete-length protein query sequences from large families, PSW's accuracy is superior to that of the other methods, but its accuracy is poor when used with partial-length query sequences. False negatives are twice as common as false positives irrespective of the search methods if a family-specific threshold score that minimizes the total number of errors (i.e. the most favorable threshold score possible) is used. Thus, sensitivity, not selectivity, is the major problem. Among the analyzed methods using default parameters, the best accuracy was obtained from SSEARCH and PSW for complete-length proteins, and the two BLAST programs, plus SSEARCH, for partial-length proteins.      

Assessing the numerical accuracy of the impedance method

The impedance method has been used extensively to calculate induced electric fields and currents in tissue as a result of applied electromagnetic fields. However, there has previously been no known method for an a priori assessment of the numerical accuracy of the results found by this method. Here, we present a method which permits an a priori assessment of the numerical accuracy of the impedance method applied to physiologically meaningful problems in bioengineering. The assessment method relies on estimating the condition number associated with the impedance matrix for problems with varying shapes, sizes, conductivities, anisotropies, and implementation strategies. Equations have been provided which predict the number of significant figures lost due to poor matrix conditioning as a function of these variables. The results show that, for problems of moderate size and uncomplicated geometry, applied fields should be measured or calculated accurately to at least five or six significant figures. As resolutions are increased and material properties are more widely divergent even more significant figures are needed. The equations provided here should ensure that solutions found from the impedance method are calculated accurately.