Ancestral Reconstruction and the Evolution of Protein Energy Landscapes

A protein's sequence determines its conformational energy landscape. This, in turn, determines the protein's function. Understanding the evolution of new protein functions therefore requires understanding how mutations alter the protein energy landscape. Ancestral sequence reconstruction (ASR) has proven a valuable tool for tackling this problem. In ASR, one phylogenetically infers the sequences of ancient proteins, allowing characterization of their properties. When coupled to biophysical, biochemical, and functional characterization, ASR can reveal how historical mutations altered the energy landscape of ancient proteins, allowing the evolution of enzyme activity, altered conformations, binding specificity, oligomerization, and many other protein features. In this article, we review how ASR studies have been used to dissect the evolution of energy landscapes. We also discuss ASR studies that reveal how energy landscapes have shaped protein evolution. Finally, we propose that thinking about evolution from the perspective of an energy landscape can improve how we approach and interpret ASR studies. Expected final online publication date for the Annual Review of Biophysics, Volume 53 is May 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Topiary: Pruning the manual labor from ancestral sequence reconstruction

Ancestral sequence reconstruction (ASR) is a powerful tool to study the evolution of proteins and thus gain deep insight into the relationships among protein sequence, structure, and function. A major barrier to its broad use is the complexity of the task: it requires multiple software packages, complex file manipulations, and expert phylogenetic knowledge. Here we introduce topiary, a software pipeline that aims to overcome this barrier. To use topiary, users prepare a spreadsheet with a handful of sequences. Topiary then: (1) Infers the taxonomic scope for the ASR study and finds relevant sequences by BLAST; (2) Does taxonomically informed sequence quality control and redundancy reduction; (3) Constructs a multiple sequence alignment; (4) Generates a maximum-likelihood gene tree; (5) Reconciles the gene tree to the species tree; (6) Reconstructs ancestral amino acid sequences; and (7) Determines branch supports. The pipeline returns annotated evolutionary trees, spreadsheets with sequences, and graphical summaries of ancestor quality. This is achieved by integrating modern phylogenetics software (Muscle5, RAxML-NG, GeneRax, and PastML) with online databases (NCBI and the Open Tree of Life). In this paper, we introduce non-expert readers to the steps required for ASR, describe the specific design choices made in topiary, provide a detailed protocol for users, and then validate the pipeline using datasets from a broad collection of protein families. Topiary is freely available for download: https://github.com/harmslab/topiary.

Rapid and inexpensive preparation of genome-wide nucleosome footprints from model and non-model organisms

MNase-seq (micrococcal nuclease sequencing) is used to map nucleosome positions in eukaryotic genomes to study the relationship between chromatin structure and DNA-dependent processes. Current protocols require at least two days to isolate nucleosome-protected DNA fragments. We have developed a streamlined protocol for S. cerevisiae and other fungi which takes only three hours. Modified protocols were developed for wild fungi and mammalian cells. This method for rapidly producing sequencing-ready nucleosome footprints from several organisms makes MNase-seq faster and easier, with less chemical waste.

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A fast way to prepare micrococcal nuclease nucleosome footprints for MNase-seq

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Eliminates use of phenol and chloroform and reduces the amount of cells required

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Adaptable for a variety of organisms