Due to continual advances in sequencing and other “omics” technologies, biology is experiencing a big data revolution. Computational methods are required not only to interpret newly sequenced genomes, but search through a vast quantity of existing biological information to reveal previously uncharacterized functionality.

The Doxey lab is interested in both the development and application of computational methods to predict novel molecular functions (protein-coding and non-coding) from genomic, structural, and other high-throughput datasets. We explore three separate but overlapping areas:

Predicting novel protein families and functions

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We develop methods that combine sequence analysis with structural bioinformatics to predict and experimentally validate protein functions of interest. Currently, we are focusing efforts on predicting new families and functions of bacterial flagellins, clostridial toxins, and proteolytic enzymes.

Selected Papers

  • Lobb B, Doxey AC. (2016) Novel function discovery through sequence and structural data mining. Current Opinion in Structural Biology, 38:53-61. [pubmed]
  • Mansfield M, Adams J, Doxey AC. (2015) Botulinum neurotoxin homologs outside of Clostridium. FEBS Letters, 589:342-8. [pubmed]
  • Doxey AC, McConkey BJ. (2013) Prediction of molecular mimicry candidates in human pathogenic bacteria. Virulence, 4:1-14. [pubmed]

Predicting evolutionary adaptations in genes and genomes

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We combine sequence analysis, phylogenetics and structural modeling to pinpoint adaptive events in genes and genomes. We are interested in inferring mechanisms of neofunctionalization and functional divergence in protein families as well as non-coding regulatory elements.

Selected Papers

  • Adams J, Mansfield MJ, Richard DJ, Doxey AC. (2016) Lineage-specific mutational clustering in protein structures predicts evolutionary shifts in function. Bioinformatics, (to appear)
  • Doxey AC, Yaish MW, Moffatt BA, Griffith M, McConkey BJ. (2007) Functional divergence in the Arabidopsis beta-1,3-glucanase gene family inferred by phylogenetic reconstruction of expression states. Molecular Biology and Evolution, 24:1045-1055. [pubmed]

Comparative functional metagenomics

The Doxey Lab is also developing computational approaches to functionally annotate metagenomes and detect biologically relevant differences between them. Recent work includes the development of the MetAnnotate framework for combined taxonomic and functional profiling of metagenomic datasets.

Selected Papers

  • Petrenko P, Lobb B, Kurtz DA, Neufeld JD, Doxey AC. (2015) MetAnnotate: function-specific taxonomic profiling and comparison of metagenomes. BMC Biology, 13:92. [pubmed]
  • Lobb B, Kurtz DA, Moreno-Hagelsieb G, Doxey AC. (2015) Remote homology and the functions of metagenomic dark matter. Frontiers in Genetics. [pubmed]
  • Doxey AC, Kurtz DA, Lynch MDJ, Sauder LA, Neufeld JD. (2015) Aquatic metagenomes implicate Thaumarchaeota in global cobalamin production. ISME J, 9:461-71. [pubmed]