Accounting for ambiguity in ancestral sequence reconstruction

Engineering functional thermostable proteins using ancestral sequence reconstruction

Natural proteins are often only slightly more stable in the native state than the denatured state, and an increase in environmental temperature can easily shift the balance towards unfolding. Therefore, the engineering of proteins to improve protein stability is an area of intensive research. Thermostable proteins are required to withstand industrial process conditions, for increased shelf-life of protein therapeutics, for developing robust 'biobricks' for synthetic biology applications, and for research purposes (e.g. structure determination). In addition, thermostability buffers the often destabilizing effects of mutations introduced to improve other properties. Rational design approaches to engineering thermostability require structural information, but even with advanced computational methods, it is challenging to predict or parameterize all the relevant structural factors with sufficient precision to anticipate the results of a given mutation. Directed evolution is an alternative when structures are unavailable but requires extensive screening of mutant libraries. Recently however, bioinspired approaches based on phylogenetic analyses have shown great promise. Leveraging the rapid expansion in sequence data and bioinformatic tools, ancestral sequence reconstruction (ASR) can generate highly stable folds for novel applications in industrial chemistry, medicine, and synthetic biology. This review provides an overview of the factors important for successful inference of thermostable proteins by ASR and what it can reveal about the determinants of stability in proteins.

Using the Evolutionary History of Proteins to Engineer Insertion-Deletion Mutants from Robust, Ancestral Templates Using Graphical Representation of Ancestral Sequence Predictions (GRASP)

Analyzing the natural evolution of proteins by ancestral sequence reconstruction (ASR) can provide valuable information about the changes in sequence and structure that drive the development of novel protein functions. However, ASR has also been used as a protein engineering tool, as it often generates thermostable proteins which can serve as robust and evolvable templates for enzyme engineering. Importantly, ASR has the potential to provide an insight into the history of insertions and deletions that have occurred in the evolution of a protein family. Indels are strongly associated with functional change during enzyme evolution and represent a largely unexplored source of genetic diversity for designing proteins with novel or improved properties. Current ASR methods differ in the way they handle indels; inclusion or exclusion of indels is often managed subjectively, based on assumptions the user makes about the likelihood of each recombination event, yet most currently available ASR tools provide limited, if any, opportunities for evaluating indel placement in a reconstructed sequence. Graphical Representation of Ancestral Sequence Predictions (GRASP) is an ASR tool that maps indel evolution throughout a reconstruction and enables the evaluation of indel variants. This chapter provides a general protocol for performing a reconstruction using GRASP and using the results to create indel variants. The method addresses protein template selection, sequence curation, alignment refinement, tree building, ancestor reconstruction, evaluation of indel variants and approaches to library development.

Calculating Orthologous Protein-Coding Sequence Set Probability Using the Poisson Process

We extend the popular Jukes-Cantor evolution model and calculate the probability of an orthologous nucleotide sequence set [a reference sequence (B₁) stays with the other sequences (B_-1)], where the sequence evolution [from a last common ancestral sequence (ɑ)] follows the (prospective) Poisson process with the overall event rate λ prorated among mutation types (nucleotide/codon substitution, insertion, and deletion) and sites along each sequence. The corresponding retrospective process (reversing the prospective process) facilitates developing algorithms to calculate the marginal probability [Pr(B₁)] (Monte Carlo integration) and sample ɑ (given B₁). We calculate probability Pr(B_-1|ɑ) based on the identified events (during "ɑ→B_-1") from pairwise sequence alignment to implement Pr(B_-1|B₁) calculation (Monte Carlo integration). Event queue sampling and probability magnifiers are used to improve the computational efficiency when the number of events is large. We finally test our procedure on both simulated and recently studied hexapod transcriptome data (Brandt et al.), where each asexual lineage pairs with its closest related sexual lineage. Rate estimates (for Phasmatodea and Zygentoma) and model comparison indicate that the asexual lineages likely mutate several times faster than their sexual relatives.

Ancestral sequence reconstruction for protein engineers

In addition to its value in the study of molecular evolution, ancestral sequence reconstruction (ASR) has emerged as a useful methodology for engineering proteins with enhanced properties. Proteins generated by ASR often exhibit unique or improved activity, stability, and/or promiscuity, all of which are properties that are valued by protein engineers. Comparison between extant proteins and evolutionary intermediates generated by ASR also allows protein engineers to identify substitutions that have contributed to functional innovation or diversification within protein families. As ASR becomes more widely adopted as a protein engineering approach, it is important to understand the applications, limitations, and recent developments of this technique. This review highlights recent exemplifications of ASR, as well as technical aspects of the reconstruction process that are relevant to protein engineering.

Ancestral sequence reconstruction - An underused approach to understand the evolution of gene function in plants?

Whilst substantial research effort has been placed on understanding the interactions of plant proteins with their molecular partners, relatively few studies in plants - by contrast to work in other organisms - address how these interactions evolve. It is thought that ancestral proteins were more promiscuous than modern proteins and that specificity often evolved following gene duplication and subsequent functional refining. However, ancestral protein resurrection studies have found that some modern proteins have evolved de novo from ancestors lacking those functions. Intriguingly, the new interactions evolved as a consequence of just a few mutations and, as such, acquisition of new functions appears to be neither difficult nor rare, however, only a few of them are incorporated into biological processes before they are lost to subsequent mutations. Here, we detail the approach of ancestral sequence reconstruction (ASR), providing a primer to reconstruct the sequence of an ancestral gene. We will present case studies from a range of different eukaryotes before discussing the few instances where ancestral reconstructions have been used in plants. As ASR is used to dig into the remote evolutionary past, we will also present some alternative genetic approaches to investigate molecular evolution on shorter timescales. We argue that the study of plant secondary metabolism is particularly well suited for ancestral reconstruction studies. Indeed, its ancient evolutionary roots and highly diverse landscape provide an ideal context in which to address the focal issue around the emergence of evolutionary novelties and how this affects the chemical diversification of plant metabolism.

Phylogeography of the marine pathogen, Vibrio vulnificus, revealed the ancestral scenarios of its evolution

Vibrio vulnificus is the leading cause of seafood‐associated deaths worldwide. Despite the growing knowledge about the population structure of V. vulnificus, the evolutionary history and the ancestral relationships of strains isolated from various regions around the world have not been determined. Using the largest collection of sequence and isolate data of V. vulnificus to date, we applied ancestral character reconstruction to study the phylogeography of V. vulnificus. Multilocus sequence typing data from 10 housekeeping genes were used for the inference of ancestral states and reconstruction of the evolutionary history. The findings showed that the common ancestor of all V. vulnificus populations originated from East Asia, and later evolved into two main clusters that spread with time and eventually evolved into distinct populations in different parts of the world. While we found no meaningful insights concerning the evolution of V. vulnificus populations in the Middle East; however, we were able to reconstruct the ancestral scenarios of its evolution in East Asia, North America, and Western Europe.

A Fast Likelihood Method to Reconstruct and Visualize Ancestral Scenarios

The reconstruction of ancestral scenarios is widely used to study the evolution of characters along phylogenetic trees. One commonly uses the marginal posterior probabilities of the character states, or the joint reconstruction of the most likely scenario. However, marginal reconstructions provide users with state probabilities, which are difficult to interpret and visualize, whereas joint reconstructions select a unique state for every tree node and thus do not reflect the uncertainty of inferences. We propose a simple and fast approach, which is in between these two extremes. We use decision-theory concepts (namely, the Brier score) to associate each node in the tree to a set of likely states. A unique state is predicted in tree regions with low uncertainty, whereas several states are predicted in uncertain regions, typically around the tree root. To visualize the results, we cluster the neighboring nodes associated with the same states and use graph visualization tools. The method is implemented in the PastML program and web server. The results on simulated data demonstrate the accuracy and robustness of the approach. PastML was applied to the phylogeography of Dengue serotype 2 (DENV2), and the evolution of drug resistances in a large HIV data set. These analyses took a few minutes and provided convincing results. PastML retrieved the main transmission routes of human DENV2 and showed the uncertainty of the human-sylvatic DENV2 geographic origin. With HIV, the results show that resistance mutations mostly emerge independently under treatment pressure, but resistance clusters are found, corresponding to transmissions among untreated patients.