Toward more accurate ancestral protein genotype-phenotype reconstructions with the use of species tree-aware gene trees

Mathieu Groussin, Joanne K Hobbs, Gergely J Szöllősi, Simonetta Gribaldo, Vickery L Arcus, Manolo Gouy

Research output: Contribution to journalArticlepeer-review


The resurrection of ancestral proteins provides direct insight into how natural selection has shaped proteins found in nature. By tracing substitutions along a gene phylogeny, ancestral proteins can be reconstructed in silico and subsequently synthesized in vitro. This elegant strategy reveals the complex mechanisms responsible for the evolution of protein functions and structures. However, to date, all protein resurrection studies have used simplistic approaches for ancestral sequence reconstruction (ASR), including the assumption that a single sequence alignment alone is sufficient to accurately reconstruct the history of the gene family. The impact of such shortcuts on conclusions about ancestral functions has not been investigated. Here, we show with simulations that utilizing information on species history using a model that accounts for the duplication, horizontal transfer, and loss (DTL) of genes statistically increases ASR accuracy. This underscores the importance of the tree topology in the inference of putative ancestors. We validate our in silico predictions using in vitro resurrection of the LeuB enzyme for the ancestor of the Firmicutes, a major and ancient bacterial phylum. With this particular protein, our experimental results demonstrate that information on the species phylogeny results in a biochemically more realistic and kinetically more stable ancestral protein. Additional resurrection experiments with different proteins are necessary to statistically quantify the impact of using species tree-aware gene trees on ancestral protein phenotypes. Nonetheless, our results suggest the need for incorporating both sequence and DTL information in future studies of protein resurrections to accurately define the genotype-phenotype space in which proteins diversify.

Original languageEnglish
Pages (from-to)13-22
Number of pages10
JournalMolecular Biology and Evolution
Issue number1
Publication statusPublished - Jan 2015


  • Amino Acid Sequence
  • Bacterial Proteins/genetics
  • Computational Biology/methods
  • Computer Simulation
  • Evolution, Molecular
  • Genotype
  • Gram-Positive Bacteria/enzymology
  • Phenotype
  • Phylogeny
  • Proteins/genetics


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