This Program Project focuses on the development and application of novel computational and experimental strategies for the discovery of novel metabolic pathways in microbial species for which complete genome sequences are available. The Program Project involves three Projects: 1) Metabolism Project for target selection and experimental verification of predicted in vitro enzymatic activities and in vivo physiological functions (pathways); 2) Ligand Discovery Project for large-scale screening of ligand specificities of both solute binding proteins (SBPs) for transport systems and transcriptional regulators by differential scanning fluorimetry; and 3) Modeling Project for in silico pathway docking and integrative pathway mapping to predict metabolic pathways. The Program Project involves two Cores: 1) Administrative Core to coordinate day-to-day operations and communications as well as oversee target selection; and 2) Protein Core for high-throughput gene cloning from gDNAs, protein expression, and protein purification to provide samples of SBPs and transcriptional regulators for ligand screening by the Ligand Discovery Project and of pathway enzymes for in vitro enzymatic assays by the Metabolism Project. The Program Project has four Specific Aims focused on developing an integrated general strategy for the discovery of pathways that is expected to be broadly applicable: 1) large-scale screening of families of SBPs and transcriptional regulators with small molecule ligand libraries, with the goal of assigning ligand specificities and describing specificity/sequence space in the families; 2) prediction of novel metabolic pathways using homology modeling to obtain structures for pathway enzymes (identified from genome neighborhood context of the SBPs and transcriptional regulators), in silico ligand docking of small molecule libraries to obtain hit lists of substrates for all enzyms in the pathway (pathway docking), and integrative pathway mapping to identify an optimized pathway using clues from SBP specificity, pathway docking hit lists, a library of chemical reactions, and similarity ensemble analysis; 3) verification of the predicted pathways using in vitro enzymatic activities, growth phenotypes, genetics, transcriptomics, and metabolomics; and 4) transfer of annotations to UniProt for dissemination and use in improving the quality of automatic functional annotations for newly sequenced genomes. The Program Project will illustrate this strategy with a focus on discovery of carbohydrate and amino acid catabolic pathways in Firmicute species found in the human gut microbiome.
A genome sequence should allow the complete set of encoded metabolic pathways to be deciphered. We propose that the ligand specificities of solute binding proteins for transport systems and transcriptional regulators can be used to identify the substrates for pathways and, also, predict substrates, intermediates, products, and enzymes in the pathways. This strategy should be broadly applicable, including for species in the human gut microbiome.
|Gerlt, John A (2017) Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions. Biochemistry 56:4293-4308|