Eric Gaucher, Associate Professor
Ph.D., Evolutionary & Biomedical Sciences, University of Florida, 2001
Office: Cherry Emerson (CE) 311
Evolutionary synthetic biology, molecular biology, comparative genomics, computational biology, bioinformatics, biomedicine, molecular evolution and origins of life
Ancestral Sequence Reconstruction/Resurrection
The recent accumulation of genomic data, combined with advances in evolutionary theory and computational power, has paved the way for innovative approaches to understand the origins, evolution, and distribution of life on Earth. One such approach to understand ancestral states follows a present-day-backwards strategy, whereby genomic sequences from extant (modern) organisms are incorporated into evolutionary models that estimate the extinct (ancient) character states of genomes no longer present on Earth. These inferred ancestral gene sequences act as hypotheses that can be tested in the laboratory through the resurrection of the ancestral proteins themselves.
To date, our laboratory has resurrected proteins on the order of 3.5 billion years old. These ancient proteins allowed us to better understand the paleoenvironment of early life on Earth.
Experimental Evolution and Experimental Phylogenies
Ancient resurrected proteins provide an opportunity to 'replay' the molecular tape of life. This research exploits our previous work with resurrected Elongation Factors proteins and the known selective constraints governing the thermodynamic properties of modern proteins in their modern hosts. Recombinant bacteria in which their modern Elongation Factor is replaced with an ancient Elongation Factor will be subjected to long-term experimental evolution studies to monitor the adaptation of the ancient biomolecule. This research allows us to answer questions regarding adaptive landscapes and functional sequence space.
Directed Evolution and Protein Engineering
Directed evolution has been widely employed to enhance protein structural stability and activity, expand functionality and alter specificity. We have developed a novel approach for generating libraries of variant genes that takes advantage of the evolutionary history of a gene family by generating a combinatorial library incorporating amino acid replacements inferred during episodes of adaptive evolution. We have termed this approach 'Reconstructing Evolutionary Adaptive Paths' (REAP). The utility of the REAP approach has already been validated with DNA polymerases by engineering the substrate binding pocket to accept non-standard nucleosides during DNA synthesis.
Computational analyses are an integral component of our research and serve multiple roles. On the one, computation guides our biochemical and molecular biology experiments. On the other, computation is used for comparative genomic studies and to develop models of molecular sequence evolution and protein structure evolution. These include models to understand the functional divergence of genomic sequences, detection of single nucleotide polymorphisms (SNPs) within the context of clinical genetics, protein stability and thermodynamics during evolutionary history, among others.
The long-term goal of this research theme is to develop and demonstrate the value of comparative evolutionary genomic tools needed to understand human disease and develop therapeutics. These tools are needed to fully exploit the potential of current genomic sequence data, and guide the collection of new data. They will join ideas, data and technology from evolutionary theory, earth science, organismic biology and organic chemistry, and exploit the natural history captured within genomic sequences themselves. Along these lines, we are attempting to understand the history and role of uric acid in mammals, why uricase is a pseudogene in some primates, and the possible therapeutic value of ancient resurrected uricases.
Along similar lines, we are engineering components of the protein translation system intended to enhance incorporation of un-natural amino acids during protein synthesis. The expanded repertoire of protein functionality could lead to novel therapeutics.
Gaucher, E.A., Kratzer, J.T., R.N Randall (2010). Deep phylogeny-how a tree can help characterize early life on Earth. Cold Spring Harb Perspect Biol. 2(1): a002238.
Chen F, Gaucher E.A., Leal N.A., Hutter D., Havemann S.A., Govindarajan S., Ortlund E.A., S.A Benner(2010). Reconstructed evolutionary adaptive paths give polymerases accepting reversible terminators for sequencing and SNP detection. Proc Natl Acad Sci U S A. 107(5):1948-53.
Gaucher, E. A., Ganesh, O. & S. Govindarajan (2008). Paleotemperature trend for Precambrian life inferred from resurrected proteins. Nature, 451: 704-707.
Johnson, R. J., Gaucher, E. A., Sautin, Y. Y., Henderson, G. N., Angerhofer, A. J., and S. A. Benner (2008). The planetary biology of ascorbate and uric acid and their relationship with the epidemic of obesity and cardiovascular disease. Med Hypotheses. 71:22-31.
Benner, S. A., Sassi, S., and E. A. Gaucher (2007). Molecular Paleoscience. Systems Biology from the Past. Adv. Enzymol. Relat. Areas Mol. Biol. 75:1-132.
Phillips, S. E., Vincent, P., Rizzieri, K. E., Schaaf, G., Bankaitis, V. A., and E. A. Gaucher (2006). The diverse biological functions of phosphatidylinositol transfer proteins in eukaryotes. Crit. Rev. Biochem. Mol. Biol. 41:21-49.
Li, T., Chamberlin, S. G., Caraco M. D., Gaucher, E. A., Liberles, D. A., and S. A. Benner (2006). Transition redundant approach-to-equilibrium analysis of gene sequences: Tools to date events in the genomic record. BMC Evol. Biol. 6:25.
Gaucher, E. A., De Kee, D. W., and S. A. Benner (2006) Application of DETECTER, an evolutionary genomic tool to analyze genetic variation, to the cystic fibrosis gene family. BMC Genomics 7:44.
Thomson, J. M., Gaucher, E. A., Burgan, M. F., Li, T., Aris, J. P. and S. A. Benner (2005). Resurrecting ancient alcohol dehydrogenases from Yeast. Nature Genetics 37:630-635.
Gaucher, E. A. and M. Miyamoto (2005). A call for likelihood phylogenetics even when evolution is heterogeneous. Molecular Phylogenetics & Evolution 37:928-931.