Gill Group Webpage

University of Colorado

Department of Chemical and Biological Engineering

Laboratory of

Evolutionary and Metabolic Engineering

Research Overview

Our research falls within the general fields of Metabolic Engineering and Directed Evolution. The overarching objective of our research is to develop new genetic and genomic tools and applications to improve fundamental understanding of the evolution and engineering of relevant traits in bacteria of industrial and clinical relevance. We are currently pursuing this objective within the context of bacterial stress tolerance traits, which are broadly significant across many metabolic engineering applications including industrial fermentations, bioremediation, and antibiotic resistance among others.

Our research attempts to integrate so-called “forward/rational” and “reverse/evolutionary” strategies for strain engineering. Projects include i) fundamental studies that compare different methods for strain engineering, for example the affect of recombination vs no-recombination in classic strain engineering, ii) developmental efforts focused on the creation of new genetic vectors or applications of DNA microarray technologies, and iii) applied studies focused on the discovery of genes that improve E. coli growth and/or stress tolerance or increase P. aeruginosa sensitivity to antibiotics. Our efforts are currently supported by several research grants from the National Science Foundation, National Institutes of Health, the Cystic Fibrosis Foundation, and the Butcher Foundation as well as collaborations with Agilent, Inc. and Cargill, Inc..

Our research laboratory is located within the newly opened Discovery Learning Center. The DLC is a unique facility designed around the idea of research as a valuable learning tool. The focus is on vertically integrated research teams where faculty mix with post-docs, graduate, undergraduate, and even high school students in a collaborative effort to address specific research goals.

Projects

Stress Tolerance of E. Coli (T. Warnecke)

We have developed Mixed Library Parallel Gene Trait Mapping (ML-PGTM) as a technique that identifies the effect of specific trait-conferring genes on phenotype. We have utilized this method to select for tolerance in E. Coli to ethanol and 3-hydroxy propionate. Chemical stress was used as a selective environment to identify the most tolerant clones originating from a mixture of plasmid–based genomic libraries with varying insert sizes. Selected transformants exhibited increased minimum bactericidal concentrations of these chemicals in minimal media using genomic libraries with 0.5kb, 1kb, 2kb, 4kb and 8kb insert sizes. Plasmid population composition was examined with DNA micro-array technology. After subsequent analysis, genes and operons conferring tolerance were identified and confirmed.

Metabolic Engineering Bacteria to Produce Human Drug Metabolites (J. Prior)

Microbial models for human drug metabolism that contain major drug metabolizing enzymes are being developed to replace many of the traditional methods such as the use of animal models or liver microsomes. There are several strains of bacteria that have been found to produce many of the same metabolites of different drugs as humans do. One of these, Actinoplanes sp. ATCC 53771, is currently being used to produce several metabolites of sirolimus, a macrolide immunosuppressant. The bacterium is not well characterized and has poor growth conditions, making it difficult to produce large quantities of the metabolites for further study. The Actinomycetes are well known for containing cytochrome P450 systems, which leads us to believe that a cytochrome P450 enzyme in Actinoplanes sp. is responsible for the metabolism of sirolimus. Several DNA fragments of P450s from Actinoplanes have been identified and are currently being extended to isolate the entire genes. The genes can then be cloned and expressed in E. coli that grows faster and under more desirable conditions for the production of sirolimus metabolites.

Integrating multiple tools and data sources for the construction of protein functional networks (A. Karimpour-fard)

In recent years, several computational methods for predicting function beyond the homology approach have been developed. Computation methods such as sub cellular localization, post-translational modification, and protein-protein interaction allow us to predict the function of uncharacterized proteins. I am developing an integrated tool to look at the result of protein-protein interaction databases using a genomic context approach. Methods of inference used include Rosetta Stone , Phylogenetic Profiles , Gene Neighbor and Gene Cluster.

Using Genome Shuffling in Escherichia coli to Improve Naphthalene Oxidation (S. Ziesman)

The overall aim of my inverse metabolic engineering research project is to improve understanding of the mechanisms affecting the engineering and evolution of traits transferred from natural to industrial host strains. This project is focused on improving the conversion of naphthalene into 1-naphthol, a conversion which is traditionally performed chemically, as a model system for examining the mechanisms underlying phenotypes obtained by genome shuffling. Toluene ortho-monooxygenase (TOM) from Burkholderia cepacia G4 catalyzes naphthalene oxidation, as well as oxidation of chlorinated ethenes and toluene, but TOM is not naturally expressed by Escherichia coli. Genome shuffling is a powerful tool, enabling directed evolution of superior strains through the genetic recombination of a genetically diverse collection of mutants. Genome shuffling is advantageous when compared with classic strain selection because of an improved ability to eliminate deleterious mutations and accumulate beneficial mutations. We will describe the current status of our efforts in this project, including: (i) genome shuffling of two different auxotrophic E. coli strains to demonstrate the technique in gram-negative bacteria, (ii) implementation of a high-throughput screen to detect single colonies of bacteria that produce higher levels of 1-naphthol, (iii) insertion of the TOM gene cluster into the E. coli chromosome, and (iv) genome shuffling of this E. coli strain. Future work includes the use of several microarray-enabled approaches to identify and compare the genetic basis of improved 1-naphthol production phenotypes obtained by genome shuffling.

Restoring Sensitivity in Antibiotic Resistant Bacteria (J. Struble)

The overall objective of this project is to "inverse" metabolically engineer antibiotic sensitivity back into antibiotic resistant P. aeruginosa. We are employing several different methods in this project that involve genome shuffling / library screening to identify strains with increased sensitivity along with microarrays and conventional gene sequencing to identify the genetic basis underlying increased sensitivity phenotypes.

Understanding Phenotypes using Functional Genomics (M. Lynch, P. Bevins)

The overall objective of this work is to develop and utilize functional genomic tools in order to better understand the genotypic basis of interesting phenotypes. In particular we have developed library and disruptive genomic techniques, in the aid of understanding antibiotic resistance mechanisms in Pseudomonas aeruginosa and biofilm development in Escherichia coli.

Creating an in situ, spotted microarray for Burkholderia cenocepacia (D. Leiske)

With the support of the Cystic Fibrosis Foundation and Agilent Technologies, we are primarily concerned with the design and validation of an in-situ, inkjet microarray for the opportunistic pathogen Burkholderia cenocepacia (J2315). Past work has involved the successful design of an 8.4K spotted microarray, validated through experimental trials. Recently, we have completed the design of an 11K microarray for all strains of B. cenocepacia, genomavar III. Future work will focus on evaluating this novel microarray.

Engineering succinic acid tolerance in E. coli for improved productivity (A. Singh)

Succinate is one of the important platform chemicals included in the USDOE list of top value added chemicals. It can be produced biochemically by engineered microbes but its toxicity to the host organism severely limits the productivity. The overall objective in this project is to identify the genes conferring tolerance to succinate toxicity using SCALEs, a powerful library based technique developed in our lab. We ultimately intend to engineer the identified tolerance genes to a succinic acid production strain for improve productivity.

Contact Information: Ryan Gill

Telephone:

303-492-2627

Address:

University of Colorado @ Boulder

ECCH120/UCB424

Boulder, CO 80309

Email:

rtg@colorado.edu